an assessment of location data requirements in logistics

Int. J. Process Management and Benchmarking, Vol. 3, No. 2, 2013 173

Copyright © 2013 Inderscience Enterprises Ltd.

An assessment of location data requirements in logistics

Ahmed Musa* Lancashire Business School, University of Central Lancashire, Preston PR1 2HE, UK Fax: +44(0)1772892906 E-mail: [email protected] *Corresponding author

Angappa Gunasekaran Department of Decision and Information Sciences, Charlton College of Business, University of Massachusetts-Dartmouth, North Dartmouth, MA 02747-2300, USA E-mail: [email protected]

Yahaya Yusuf Lancashire Business School, University of Central Lancashire, Preston PR1 2HE, UK E-mail: [email protected]

Samuel Azua and Youngu Terwase Department of Geomatics, Ahmadu Bello University, Zaria 880001, Nigeria E-mail: [email protected] E-mail: [email protected]

Abstract: In the geolocation and navigation community, requirements for location data are often expressed in terms of accuracy, integrity and availability of location information in both time and space. The question arises as to what these requirements are across the application spectrum in logistics and the technologies available to meet the needs. The answer to this question is not as straightforward as it might first seem, given the diversity of potential applications and the plethora of technologies currently available, or are being developed, to meet various industrial needs. Based on a specially-designed Delphi study with experts across industries, this paper provides some specific information and guidance in this regard. The results presented in this paper can be used by the logistics, geolocation and semiconductor industries alike in identifying the geolocation needs of their various applications and how those needs can be fulfilled.

174 A. Musa et al.

Keywords: location awareness; logistics; supply chain management; RFID; tracking and tracing.

Reference to this paper should be made as follows: Musa, A., Gunasekaran, A., Yusuf, Y., Azua, S. and Terwase, Y. (2013) ‘An assessment of location data requirements in logistics’, Int. J. Process Management and Benchmarking, Vol. 3, No. 2, pp.173–212.

Biographical notes: Ahmed Musa holds a PhD from the University of Newcastle upon Tyne, UK. He is a Researcher in Logistics and Operations at Lancashire Business School, University of Central Lancashire, Preston, UK, and a member of the University’s Institute of Logistics and Operations Management. He has research experience in engineering and management. Currently, his research activities are focused on agility, risk and resilience in strategic networks; oil and gas operations; energy supply chains; and optimal and autonomous control in logistics and operations.

Angappa Gunasekaran is the Dean of Charlton College of Business, University of Massachusetts Dartmouth, USA. He received his PhD in Industrial Engineering and Operations Research from the Indian Institute of Technology, Bombay. He was the Chairperson of the Department of Decision and Information Sciences, Charlton College of Business, from 2006 to 2012. His articles have been cited in over 13,000 articles, most of which are in prestigious journals. He is the Editor-in-Chief of several journals and has guest-edited special issues for a number of highly rated journals. He is also on the editorial boards of more than 20 peer-reviewed journals.

Yahaya Yusuf holds a PhD in Operations Management from the University of Liverpool, UK. He is a Professor at Lancashire Business School, University of Central Lancashire, Preston, UK, and the Director of the University’s Institute of Logistics and Operations Management. His main research interests are in agile manufacturing, supply chain agility, sustainable operations and supply chains, and decision support systems for logistics and operations management. His research has been supported by grants from the UK’s Engineering and Physical Science Research Council (EPSRC) and industry. He is a member of the EPSRC Peer Review College and on the editorial boards of three prestigious journals.

Samuel Azua is a Lecturer in the Department of Geomatics, Ahmadu Bello University, Zaria, Nigeria. He holds a Master’s degree from the University of Lagos, Nigeria, and is currently a PhD student in the West African Regional Centre for Training in Aerospace Surveys, Ile-Ife, Nigeria. His current research interests include location determination by satellite signals, and use of geospatial data for environmental, social and economic studies.

Youngu Terwase is a Lecturer in the Department of Geomatics, Ahmadu Bello University, Zaria, Nigeria. He holds a Master’s degree from the University of Lagos, Nigeria, and is currently a PhD student in Ahmadu Bello University, Zaria. His current research interests include high-precision and mobile-computing related positioning using hybrid technologies.

An assessment of location data requirements in logistics 175

1 Introduction

The geographic location of an object may be defined with respect to a global or local frame of reference. The frame of reference itself may be based on any given system of coordinate, examples of which include rectangular (Cartesian), spherical, ellipsoidal, and physical (gravitational potential) coordinate system (Moon and Spencer, 1988). By ‘location data’, we mean the following equation:

location data location coordinates accuracy continuity availability= + + +

The accuracy of location reflects how close its coordinates are to their true/errorless value. In some cases it may simply be an indication of the internal consistency of the measurement system, while in other situations it may represent a deviation of the measured value from a known external standard. The integrity of location is usually a reflection of the confidence that is associated with the reported value. Confidence may be expressed by the probability that the given value is within the true value, such as saying the location is known to twice its standard deviation 95% of the time. Continuity implies that the location value will not change until a certain time, if ever, despite changes in the ambient measurement environment (e.g., weather). Availability means that the infrastructure (e.g., satellite signals) used to determine the location will be available at some point in the future to repeat the measurements that led to the location value. Continuity and availability both indicate the repeatability of the given location value.

Geolocation is the identification of the geographic location of an object, such as a vehicle, mobile phone, or an internet-connected computer terminal. Geolocation may refer to the routine of evaluating the location, or to the actual measured location. Geolocation is closely related to the use of positioning systems and technologies to find location, but location can be discriminated from positioning by, for instance, a greater emphasis on determining a meaningful location (e.g., a street address) rather than just a set of geographic coordinates. Geolocation is also defined in the terms and definitions standardised by ISO/IEC 19762-5:2008 for automatic identification and data capture (AIDC) techniques (ISO/IEC, 2008).

For either geolocating or positioning, a range of methods and technologies are available to find the location, the best known today perhaps being GPS. Internet and computer geolocation can be performed by associating a geographic location with the Internet Protocol (IP) address, MAC address, RFID, hardware embedded article/production number, embedded software number (such as UUID, Exif/IPTC/XMP or modern steganography), invoice, WiFi positioning system, or device’s GPS coordinates, or other, perhaps self-disclosed, information. In some IT applications, geolocation usually works by automatically looking up an IP address on a WHOIS service and retrieving the registrant’s physical address.

Location information is needed for several applications in logistics and supply chain management. To sufficiently contextualise the discussion, we first describe in some detail what is implied in this paper by logistics. Outside the supply chain literature, logistics is often conceived and seen in the narrow sense as a resource mobilisation problem, namely, the effective optimisation of processes and resources associated with the deployment or movement of people, goods and services such that project outcomes and end-deliveries are accomplished in good time, to the right locations, in the correct quantity, order and condition, and at optimal cost. It is often assumed that these

176 A. Musa et al.

conditions are necessary and sufficient for the total satisfaction of the end customer or beneficiary of the logistics function. In supply chain management, however, there are many other issues that come into play in the matter of logistics. These include adequate information flow within the chain; managerial and resource integration of trading partners that make up the supply chain; security of goods, services and information; efficiency and optimal operation of production and distribution systems; and the inevitable demand and supply uncertainties. However, it would appear judicious to limit this paper to considering logistics as purely a resource distribution problem for which decision support systems are always required (Shim et al., 2002). In this context, this paper examines the roles of both location determination and knowledge of location as inputs in decision support systems for global and local logistics. The main motivation for location determination in logistics is to provide visibility and hence control of processes and resources, and it transpires that process and resource visibility is an essential enabler of efficiency and security in local and global production and distribution systems. Visibility of product and asset can yield the benefits of decreased cycle times, complete prevention of handling faults and shrinkages, reduction of non-value-adding activities, and cost-effective product recalls.

Local or indoor logistics refers to the distribution problem within a restricted geography such as a factory shop-floor, a manufacturing plant, a warehouse or distribution centre, a retail store, or a shopping complex. Global or outdoor logistics refers to the orthogonal complement of the restricted geography (i.e., geographies ranging from a city to the whole of the earth’s surface). The location methods and technologies required (and the associated challenges) in these geographies often overlap but are not always the same. One key benefit of using the knowledge of location to effectively automate and manage logistics is the significant reduction in the impact of logistics on the environment, a recurring and important theme of many governments and corporations around the world. This paper focuses on requirements for location and navigation data and on the mechanisms for obtaining the needed information. The paper also briefly considers the links between logistics and location-based services, a growing area of interest to the logistics community.

Irrespective of its construct and the intrinsic industry, the main purpose of logistics is to serve the supply chain. Supply chains come in many forms and shapes. The supply chain is a complex network of trading partners (buyers and suppliers) between the primary supplier and the end customer. The Toyota motor company, for example, has over 200 direct suppliers providing about 2 billion components of 0.15 million kinds per annum. Most of these components have to be tracked and, if recalls happen, traced from the OEMs (original equipment manufacturers) to the final assembly and beyond. Reverse logistics also requires effective tracking and tracing.

In this paper, we view logistics as a physical distribution or transportation problem, ignoring other important aspects of the logistics function, such as demand and supply uncertainties, manufacturing capacity and facility location and relocation, production planning and scheduling, information flow, supply chain governance structures, value generation and regeneration in supply chains, performance measurement metrics, outsourcing, volatilities and fragilities in supply chains, human resource management, the legal environment and mandates, enabling technologies, etc. (van Eijs, 1994; Singh, 2003; Zographos, 2003; Yang, 2007; Williamson, 2008).

Dynamic fleet management and similar transport optimisation problems benefit directly from location systems (in fact, they rely on the knowledge of location), but while


we shall discuss the relevant location technologies and methodologies, we shall not delve into the operations (or operational) research issues connected with fleet telematics and management. There are dozens of such problems and proposed solutions of transport route optimisation and resource mobilisation (Grasman, 2006; Friesz, 2007; Zeimpekis et al., 2007; Nagy and Salhi, 2007). Suffice it to say here that knowledge of instantaneous location can help to reduce the complexity of transport route optimisation problems by replacing batch optimisation by one that uses dynamic vehicle location data.

Logistics is a strategic imperative for firms, especially for multinational corporations (Muckstadt and Roundy, 1993). The logistics costs of pharmaceuticals, manufacturing, and merchandising are roughly 5%, 15%, and 26%, respectively. Transportation in the UK, for example, accounts for more than 8% of GDP. In the USA, given the wide geographic extent of the country and the size of its economy, the figure is much higher, approaching almost 12% (Waters, 2003). These figures demonstrate the importance of minimising logistics costs in supply chain operations. Because of globalisation, just-in-time production and distribution, electronic commerce, the continuing growth in bundled logistics services, etc., an efficient distribution and logistics function is now recognised as the new competitive advantage and a strategic prerequisite for the success of firms.

In supply chain and production logistics, the availability of location information can help in reducing inefficient search activities and their negative impact on overall process performance. Moreover, location information also provides a basis for innovative dispatching heuristics that further optimise the scheduling of production runs with respect to various performance indicators, e.g., mean cycle time, asset utilisation, etc. Production flexibility in the form of the ability to coordinate and to control a broad number of process parameters at low costs is another important strategic advantage in a highly competitive and customer driven market.

The location methods and technologies for global (outdoor) and local (indoor) logistics do overlap in many ways but they are not always the same. For reasons of signal availability, attenuation or outright non-availability, severe multipath effects, and achievable or required accuracies, some of the technologies are suitable only in one of the operational domains (outdoor or indoor). GNSS is the natural choice for providing position and navigation data in logistics, but signal outages do occur even in outdoor environments, especially in urban canyons, underground parking lots, and under tunnels. Operational requirements usually necessitate the combination of the available technologies in a specific form of sensor fusion. In the following sections we discuss the location requirements in logistics and the localisation schemes available for meeting the requirements in outdoor/global and indoor/local logistics.

This paper documents the location requirements in logistics from ‘Delphi surveys’ of logistics and navigation industry experts and companies in the UK and USA. The paper is organised as follows. The meaning of ‘Delphi surveys’ is given in Section 2.2. Section 2 presents the motivation for the research and the method of its implementation. Section 3 presents and discusses the results of the research, namely, the requirements for location in various application domains of logistics (land transport, civil aviation, marine navigation, and indoors). Section 4 discusses the technologies that currently exist to meet the location requirements identified in Section 3. Section 5 concludes the paper. Some of the issues for future research are described in Section 5.1. The Appendix contains the list of abbreviations and their meaning.

178 A. Musa et al.

1.1 Specific benefits of location and visibility in logistics

To underscore the importance of location data in logistics, Table 1 lists some particular benefits of location, communication and visibility in logistics. All the examples shown in the table contribute to the overall logistics system efficiency and to reducing the impact of logistics on the environment. Table 1 Some specific advantages of location and visibility in logistics

Benefit Note

Improved tractor and trailer deployment

Remote asset-management technologies enable better use of existing tractors and trailers by increasing utilisation frequency, maximising loads, and reducing excess detention. These lower the costs of buying and leasing the vehicles. CSMG (2009) suggested that the average trucking customer is able to boost trailer utilisation by as much as 5% per annum, thereby reducing new trailer purchases by an average of 20% per annum over a five year period and reducing the number of trailers rented every year by up to 60%.

Fuel savings Fuel price hikes is one of the major challenges faced by logistics outfits as they add to pressures on their profits. On average, by deploying mobile asset management technologies, trucking companies can achieve fuel cost reductions on the order of US$500 to US$1,000 per tractor per year. CSMG (2009) reports a case study in which a truckload haulier operating 3,000 trailers and 1,100 tractors achieved a significant return on investment in less than a year by achieving a US$1.9 million reduction in capital spending and US$1.8 million saving in operating costs within the same period. CSMG (2009) suggested that adopters of mobile asset management technologies could realise superior performance in takings per share, by up to 25% per year as compared with the accomplishment of companies that are yet to deploy those technologies.

Agile delivery schedules and rescheduling enabled by end-to-end visibility

Status and progress reports on the movement of goods in transit keep all supply chain players informed of delays and changed delivery schedules. The value of such information increases when deliveries have to be rescheduled on short notice, since loading and unloading often have specific and limited windows. Knowledge of instantaneous location of vehicles facilitates the reduction of the complexity of vehicle routing by replacing batch optimisation by one that calls dynamic vehicle location data.

Efficient fleet management

Firms can achieve lean logistics through increased asset utilisation, right-sizing of fleets and manpower and optimised real-time vehicle routing, especially for load consolidation via merge-in-transit and cross-docking. Also, analysis of accumulated vehicle data (e.g., onboard tachograph measurements) could yield clues on vehicle and driver performance and techniques to reduce fuel consumption in subsequent operations.

Supply chain performance measurement

By analysing the passage of goods and services through the numerous stages of the supply chain, managers could garner new insights into supply chain performance challenges, e.g., by understanding the dynamics of flow of goods and services and addressing the bottlenecks. The UK’s Royal Mail has been experimenting with tracking mails for mail delivery process mapping and evaluation, with possible benefit of efficiency gains (RFID Journal, 2005).

Remote monitoring, control and command

The onboard memory and CPU capacities of sensors monitoring mobile and fixed assets are increasing on a continual basis, just as the footprints of the devices are falling as a result of improved miniaturisation, and prices are falling due to use of low-cost materials and savings from technology integration. Remote sensors are used to collect operational data, monitor cargo while in transit, and identify problems, thereby increasing process flow efficiency and reducing the possibility of losses to the industry.


Table 1 Some specific advantages of location and visibility in logistics (continued)

Benefit Note

Security and safety

High-valued cargos receive better proactive and reactive protection from real-time and driver-independent monitoring of vehicle movement and vehicle status. The movement of hazardous materials can be better monitored to enforce route compliance, avoid theft, and ensure public safety and security. Also, location-based systems have been developed for pinpointing stolen vehicles, limiting the rate at which fuel flows to their engines, gradually slowing down a stolen vehicle and avoiding potentially dangerous high-speed chase. An example of such a system is OnStar’s Stolen Vehicle Location Assistance. OnStar Corporation is a subsidiary of General Motors that provides subscription-based in-vehicle communications, security, hands-free calling, navigation, and remote diagnostics systems throughout the USA, Canada and China. In Latin American markets a similar service is known as ChevyStar.

Aerial and marine navigation

In both civil and military air and marine navigation, the needs for accuracy in position have increased dramatically in the past decade, particularly for port approach and departure. Not only are accurate positions of crafts now required with full reliability and availability, but new ADS-B (automatic dependent surveillance broadcast) systems (Figure 2) allow craft’s transponders to transmit their locations, along with other pertinent data from the craft’s flight monitoring system, to other crafts and ground stations equipped to receive the information. ADS-B ground stations tot up radar-based targets for non-ADS-B-equipped crafts to the mix and telemeter all the information back up to equipped crafts, together with information on weather and flight restrictions.

Military logistics

The mobilisation, deployment, operation, command and control of forces in the modern war theatre all require advanced logistics and localisation. Location and navigation are playing ever greater roles in military operations. Perhaps less well known is the use of localisation in autonomous land, air and sea vehicle navigation, and in ad hoc sensor networks that may be quickly deployed for covert and live operations. The Defence Advanced Research Projects Agency (DARPA) of the USA has a goal that between 2015 and 2020, 30% of its combat operations (particularly resupply operations) will be undertaken by unmanned, robotic vehicles. This has necessitated research into sophisticated real-time mobile mapping and localisation technologies in recent years (Finkelstein, 2009).

Emergency and rescue operations

Emergencies are classical logistical nightmares. They are intrinsically hard to effectively plan and prepare for, since they are usually so diverse in nature and characteristics and in such circumstances the critical infrastructure that is relied upon for normal operations is often compromised and backup systems are usually costly or impossible to install in short time scales, when the ambient environment is already challenged. Nevertheless, the availability of real-time location information about the resources that are needed to tackle emergencies can enhance mission success. Indeed modern emergency and rescue missions (irrespective of their nature) depend critically on the availability of such information. The ready availability of dynamic location information reduces the complexity of the task. Autonomous advanced decision support systems are currently being developed which will permit the virtual deployment of assets in various emergencies (Jones, 2006). Such systems assume as given the availability of real-time information about the locations and physical states of all documented assets.

180 A. Musa et al.

Table 1 Some specific advantages of location and visibility in logistics (continued)

Benefit Note Travel directions, mobile commerce, mobile advertisement, and other services based on location

These are a hotchpotch of commercial applications of location that are sometimes referred to as ‘location-based services’. They range from accessing travel directions from an onboard personal navigation device (standalone or connected via the mobile internet); getting information about traffic conditions, weather, gas price, etc., over the air (e.g., the US Department of Transportation’s SafeTrip-21 initiative); address sharing; salesmanship; roadside emergency services; locating services and facilities (e.g., restaurants, hospitals, fire hydrants) in cities; locating family, friends and pets outdoors; pay-as-you-use road toll charging; thoroughfare access control; location-based access to media such as fixed and mobile radio and TV; tracking and tracing of animals and supplies through the food chain; mobile advertisement; geotagging of pictures and audiovisual materials and products; to many more services, some of which are still emerging. For example, location enables more targeted, less intrusive, and genuinely useful information to be transmitted to a location service user. It also enables service providers to authenticate service users and restrict access to services: for instance, services may be provided or denied depending on the location of the requester (Azvine et al., 2005; Ahson and Ilyas, 2011). The FCC (the US Federal Communications Commission) prevailing mandates set requirements for mobile-originated emergency calls to be positioned in the USA so that the mobile terminal can be located to an accuracy of between 50 and 300 m for 67 to 95% of calls, depending on the location technology used (network-based or mobile terminal-based) and the location of the caller. Such requirements are fulfilled by mobile operators by using the mobile station (MS)-assisted version of Assisted-GPS (AGPS).

2 Research motivation and methodology

2.1 Motivation

Location information is needed for most activities in logistics, including: urban and national transportation, vehicle dispatch, fleet management, distribution management, retail outlet siting, customer segmentation and analysis, and dispatch rules on factory shop-floors. The chief application of location in logistics is to provide a mechanism for attaining some level of visibility (concurrent or historical) of mobile assets, inventory and personnel so as to plan, execute and monitor the effective and efficient deployment of the resources. In modern logistics, given the dynamic nature and complexity of business activities, off-shoring, outsourcing, constant change, etc., there is much priority accorded to real-time information and synchronised decision making. Real-time location information provides supply chain operators and managers (shippers, carriers, forwarders, hauliers, logistics service providers, terminal operators, retailers, and solution providers) with one important input of decision support systems for real-time inventory management, security management, and strategic decision making based on reality. Visibility and control in supply chain management are realised by location, physical condition-monitoring and mobile communication technologies. However, this paper focuses on only location, the enabling location technologies, and the standards of accuracy, integrity and availability with which location data are needed and can be provided in logistics.


Given the well-recognised potential and widespread application of location technologies in logistics (Table 1), one might be forgiven to assume that location requirements (in terms of the needed availability and accuracy) for various application scenarios in logistics have been comprehensively analysed, determined and documented. This, unfortunately, is not the case, and in view of the myriad of application domains and circumstances, the task is not as straightforward as it might first seem. The requirements indicated in this paper are based on an extensive review of both logistics and location technology literature, and on Delphi studies involving industry experts (logistics service providers, location technology providers and vendors, and academics). In discussing the location requirements in logistics, we would concentrate on the following application scenarios and assume that location information would be required to be available 90 to 95% of the time and at 95% confidence level (i.e., two-sigma level), with relatively high needs on solution integrity (i.e., quality), continuity, and system availability.

Availability is defined both in space and time as the relative percentage of a given testing interval (space or time) during which a navigation device has a valid position fix. Validity of a position fix is indeed determined by user requirements. For instance, in the case of positioning by GNSS signals, erroneous signal generation (which may originate from a combination of digital and analogue errors), deliberate spoofing, and signal multipath effects all affect satellite navigation signal quality, thus necessitating signal authentication and integrity monitoring schemes. Navigation message authentication schemes usually are based on a well-designed message structure, together with a signing and verification procedure often derived from the Rivest-Shamir-Adleman public-key algorithm in the Digital Signal Standard (RSA-DSS). The most popular integrity assertion techniques are to be found within the receiver autonomous integrity monitoring (RAIM) schemes, where snapshot procedures are common. RAIM consists of monitoring, independently at each instant of time, the projection of the error vector with the help of the least squares method of estimation (Hewitson and Wang, 2010).

Figure 1 lists some various local and global application scenarios in which location information is required in logistics. ‘Local’ here refers to applications of location and navigation data in confined or restricted spaces such as factory shop-floors, shopping complexes, and sport arenas; ‘global’ functions, in principle, have no geographic limits. Figure 1 was used as a framework to develop the Delphi questionnaire and for presenting the results in Section 3.

However, while the needs are well-known, the requisite standards and accuracies with which location information should be provided and the means to meet them (i.e., to achieve the standards and accuracies) are not documented in the logistics literature. The aim of this paper is therefore to fill these gaps. To address these issues, as a first step, empirical data was generated from the judgements and views of industry experts and analysed to arrive at the requirements for location in logistics. Analytical-cum-simulation approaches will have to consider potentially hundreds of variables and dozens of use scenarios of location in logistics and may hence be intractable for realistic cases. The judgements of the industry experts take into account their experiences and are thus, in this case, more of practical utility than theoretically derived results. The empirical methods adopted and the results reported in this paper can be used to guide simulation studies and reduce the complexity of such studies.

182 A. Musa et al.

Figure 1 Typical application scenarios requiring location information in local and global logistics

2.2 Methodology

This paper reports the results of a Delphi study of the judgements and views of the logistics, navigation, automobile, and semiconductor industry experts and companies in the UK and USA on requirements for location in logistics. The nature of the Delphi method actually used in this paper is detailed later in this section. Originally, 400 potential participants/panellists were selected through stratified sampling from various industry databases. Of the nominated 400 panellists, only 168 actually agreed to participate in the study, giving a participation rate of nearly 42%. Table 2 presents the industries of the panellists in the Delphi study, and Table 3 gives the sizes of the companies of the panellists according to the numbers of their employees. The choice of the threshold 400 was based purely on the assumption that given the experience of the potential panellists (none of them had less than ten years’ experience in their industry) and the spread of their industries, the information they provided would sufficiently reflect the needs of the logistics industry. The panellists included both industry practitioners and academics from universities. For the majority of the industrial sectors, the number of panellists who are academics was roughly half that of practitioners. The reason for the disparity between the number of practitioner and academic panellists was that this study was more focussed on practical needs than theoretical niceties. The Delphi panel discussion was conducted by e-mails between January and April 2012.

The first stage of this study was to conduct a systematic and extensive review of the existing multi-disciplinary literature on logistics, location determination, and navigation. The second stage of the study involved using a special form of the Delphi method as follows. The Delphi procedure we used consisted of preliminary inquiries sent to the potential panellists to obtain their willingness to participate in the project and provide solicited information. This was then followed by ‘Delphi by correspondence’. The questions in the questionnaire were cast to prompt adequate and fast responses from the panellists.


The Delphi method is a structured, systematic, interactive forecasting technique that relies on the views and judgements of a panel of experts. The experts answer questions in two or more rounds. After each round, a facilitator provides an anonymous summary of the experts’ opinions and forecasts from the previous round as well as the reasons they suggested for their judgements. Thus, experts are supported to revise their earlier answers in light of the responses of other panellists. It is assumed that during this process the range of the answers will shrink and the group will converge towards the ‘correct’ answer. The process is terminated after a pre-defined exit condition (e.g., number of rounds, achievement of consensus, stability of results) and the mean or median scores of the final rounds determine the results. The Delphi method is based on the principle that decisions from a structured group of individuals are more accurate than those from unstructured groups.

The traditional approach to holding a Delphi is that the panellists sit in the same venue and speak with each other in a controlled discussion. Instead of adopting this expensive routine of collecting all the panellists in the same venue, our special Delphi study was conducted by e-mail exchanges between the researchers (as facilitators or coordinators) and the panellists. This new Delphi scheme also allowed us to significantly increase the number of panellists – and hence increase the robustness of the outcome – beyond what would ordinarily have been possible by the conventional Delphi method. The panellists did not know each other, thereby removing any bias that might have been triggered otherwise. After each round of receiving responses from the panellists, outlier values of requirements for location were computed from the given responses to each requirement using the outlier detection scheme of Grubbs (1969). The outlier values and the mean of the responses to each question were then e-mailed to all the panellists whose answers happened to be outliers, with a request to them to either revise or defend their submitted values. If the panellist whose value of a requirement happened to be an outlier insisted on the validity of his or her entry rather than revise the value, such a value was then omitted from computing the current mean of the requirement. This happened in only about 2% of the questions in the questionnaire. In a few cases a panellist who has submitted an outlier value would ask for some explanation of the reasons given by the other panellists for their non-outlier values. In such a situation we would ask at least five of the panellists who have given non-outlier values to offer explanations for their judgements. We would then e-mail the explanations to the panellist who has specified an outlier value and has requested such accounts.

The opportunity given to the panellists to revise their discordant entries based on the views of other panellists is a more standard and powerful approach in empirical research than simply rejecting outlier responses. In fact, some of the techniques used for outlier detection and management (Hodge and Austin, 2004) resemble the Delphi process. For applications of location that the Delphi panellists provided no data, we used the requirements found in the literature. In such cases, the sources of the information are specifically indicated in Section 3. After the requirements were determined, we then carried out another extensive literature review, this time to map out the methods and technologies that are available to meet the current needs. Table 8 represents the outcome of this second literature review.

184 A. Musa et al.

Table 2 Industrial sectors of panellists

No. of panellists Industrial sector

Practitioners Academics Supply chain management 25 16 Logistics services 21 10 Aviation 12 5 Road transport 13 5 Rail transport 8 4 Marine transport 9 5 Geolocation services 6 3 Geolocation equipment manufacturers 4 0 Automotive OEMs and assemblers 5 0 IT/IS products and services 11 6 Subtotal 114 54 Total 168

Table 3 Sizes of companies by number of employees

Number of employees Percentage

1–50 50 51–250 20 251–500 17 501 and above 13 Total 100

3 Results and analysis

3.1 Location requirements in transportation

Location requirements in transportation vary remarkably within the various transportation modes, environments and applications (land transport, urban transport, sea transport, inland water navigation, air transport, aircraft approach and landing, seaport and airport operations, etc.), such that it is not feasible to review the needs of all the modes in this paper. However, it can readily be asserted that the most stringent requirements come from: aircraft landing; rail track matching with moving trains – the minimum centreline-to-centreline spacing between parallel tracks is 3.5 m (Simsky et al., 2004); urban transport (especially in urban public transport, route guidance, emergency and rescue operations, and commercial fleet management); and container port operations.

In container port/terminal operations, centimetre-level accuracy is needed for controlling automated guided vehicles (AGVs) and automated lift vehicles (ALVs), and for operating rubber-tired gantry cranes, rail-mounted cranes, straddle carriers, etc., for container movement and stacking. The location challenges in container stacking and in other quay and container yard operations are well-highlighted by Kim et al. (2003) and van Hees (2007).


Table 4 Land transportation location and navigation data accuracy requirements

Transport mode Accuracy (meters, 95%)

Highways Navigation and route guidance 2.5–10 Automated vehicle monitoring 25 Automated vehicle identification 25 Public safety 5–10 Resource management 30 Accident and emergency response 30 Collision avoidance 0.5–1 Transit Autonomous vehicle control 10–30 Automated voice bus-stop announcement 5 Emergency response and rescue 70–100 Transportation data collection 5 Rail Train and rail vehicle control 1 Tract defect detection and identification 0.3 Asset mapping 0.1 Emergency response and rescue 60–100 Bridge construction and bridge monitoring 0.001

Note: Some of the numerals have been rounded to whole numbers.

3.1.1 Land transportation

In land transportation the user services requiring location and navigation information include: travel and transportation management (pre-trip planning, en route driver information, route guidance, incident management, travel demand planning and management); public transport operations (public transportation management, personalised public transportation); commercial vehicle operations (advanced and automated commercial fleet planning and management); emergency and rescue operations (emergency vehicle dispatch and management, emergency alert and personal safety); and advanced vehicle control and safety systems (in-vehicle signing for situation awareness). Table 4 provides the land transportation location and navigation data accuracy requirements as deduced from the Delphi study. The requirements reflect absolute position (as opposed to relative position) needs and include those needed for infrastructure development.

3.1.2 Fleet telematics and management

In fleet telematics and commercial transportation management, the needed horizontal location accuracy is usually in the range of 1 to 40 m at two-sigma level with high integrity, continuity and availability. These results correlate with those suggested by Goel (2008), Quddus (2006), and Quddus et al. (2006a, 2006b). Typically, bus priority

186 A. Musa et al.

provisioning requires a two-dimensional location accuracy of 5 m at two-sigma level with guaranteed integrity. In urban areas, this accuracy is often difficult to attain to the requisite availability standards even with the incorporation of supplementary data sources (such as assisted GPS and feature/map aiding) into conventional GNSS and INS location algorithms.

3.1.3 Vehicle infrastructure integration

In the framework of the nascent concepts of vehicle infrastructure integration (VII) and associated dedicated short-range communication (DSRC) for transportation management (Bilchev et al., 2004), location requirements are much higher. This is usually because of the need to precisely identify the lane on which a vehicle is cruising in close proximity to other vehicles, together with the need to know its speed, acceleration and heading. IVS for situation awareness (i.e., bringing road signs, warnings and traffic conditions to the attention of the driver via onboard electronic interfaces) also places stringent requirements on the location of vehicles. V2X is the group of common underlying system components of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. V2X and advanced driver assistance system (ADAS) applications differ remarkably in their position accuracy and availability needs. Forward collision warning (FCW) and lane change advisor (LCA) require higher accuracy in location because they must identify same-lane vehicles. Emergency electronic brake light (EEBL), on the other hand, only requires identification of same-road vehicles. Some ADAS applications require accurate location information in an absolute sense, while others may function with location information that is only relatively accurate. Almost all V2V features may function properly with only relative location information (relative location and orientation of surrounding vehicles). However, almost all V2I applications need absolute location information so as to adequately orient roadway features with vehicle location.

The Research and Development Unit of General Motors uses the following classification of location information accuracy needs (Basnayake, 2009): which road, better than 5 m; which lane, better than 1.5 m; and where in lane, better than 1 m. This classification is used in expressing both relative and absolute accuracies. See also Bilchev et al. (2004), Warren (2004), and Hsu et al. (2007).

3.2 Location requirements in civil aviation

In the case of aircraft navigation and guidance, we shall focus on only civil aviation requirements. In fact, tactical air operations have important similarities to civil aviation in the four phases of en route (including oceanic and remote areas), terminal, approach and landing, and surface. The main differences between tactical air operations and civil aviation are in the areas of air manoeuvrability, speed, payload discharge and guidance, and precautions for crew safety in enemy territory.

Rather than ask the Delphi panellists to suggest the necessary accuracy, reliability and availability requirements for civil aviation, we asked them to confirm their agreement or otherwise with the ICAO standards for Navigation Service Levels APV-I, APV-II, CAT-I, CAT-II and CAT-III, all of which are described below. We also requested them to confirm their agreement or otherwise with the contents of Tables 5 and 6, both of which relate to Automatic Dependent Surveillance Broadcasts (ADS-B). All the Delphi panellists responded that, given the adoption process of the ICAO standards and


recommended practices, it was not necessary or sensible for anyone to suggest changes to the standards and recommended practices outside ICAO. Hence, the results reported in this section pertain only to ICAO standards and recommendations.

Standards and Recommended Practices (SARPs) are technical specifications adopted by the Council of ICAO in line with Article 37 of the Convention on International Civil Aviation (CICA) so as to attain the highest possible level and extent of uniformity in regulations, standards, procedures and structure regarding aircraft, personnel, airways and auxiliary services to simplify and enhance air navigation. SARPs are published by ICAO in the form of Annexes to the Chicago Convention. Annexes are not international treaties and hence SARPs lack the same legal weight as the Chicago Convention. Additionally, States agreed to “undertake to collaborate in securing ... uniformity”, not to “comply with” SARPs. Each Contracting State is entitled to advise the ICAO Council of differences between SARPs and its own local regulations and practices. Those differentiations are published in the form of Supplements to Annexes.

A standard is defined by ICAO as “any specification for physical characteristics, configuration, material, performance, personnel or procedure, the uniform application of which is recognized as necessary for the safety or regularity of international air navigation and to which Contracting States will conform in accordance with the Convention” (Milde, 2008). A Recommended Practice is defined by ICAO as “any specification for physical characteristics, configuration, material, performance, personnel or procedure, the uniform application of which is recognized as desirable in the interest of safety, regularity or efficiency of international air navigation and to which Contracting States will endeavour to conform in accordance with the Convention”. ICAO authenticates observance of SARPs through audits of State’s oversight structures and practices. Universal Safety Oversight Audit Programme (USOAP) and Universal Security Audit Programme (USAP) are the two extant audit schemes.

Unaided GPS is capable of providing aerial navigation (RNAV) en route and terminal navigation to position an aircraft in the vicinity of an airport. For landing, the aircraft electronics system switches to approach navigation. Approaches are classified as either ‘precision’ or ‘non-precision’, depending on the accuracy and functionalities of the available navigational aids. Precision approaches use both lateral (course) and vertical (glide slope) guidance to a decision height. If the needed visual references, such as the approach lights or the runway environment, are not in good view at this height, the pilot must fly a ‘missed approach’, which is a prescribed, controlled routing away from the runway.

Non-precision approaches provide lateral (course) guidance only, using a ‘minimum descent height’. This height is defined as the height below which an aircraft must not descend until and unless visual reference has been confirmed. It is typically between 75 m (250 ft) and 150 m (500 ft), depending on the airport in question. Unaided GPS is capable of providing non-precision approach, commonly referred to as lateral navigation (LNAV). On an LNAV approach, the pilot flies the final approach using lateral guidance, but when the aircraft reaches the final approach threshold, the pilot descends to a minimum descent height using the barometric altimeter. Satellite-based augmentation systems (SBAS) provide the additional capability for the aircraft to use GPS for vertical navigation (VNAV). LNAV/VNAV is an approach in which a vertical glide slope guides the aircraft to a distance of about 1,140 m (3,800 ft) before the runway limit, which is at an average decision height of 105 m (350 ft).

188 A. Musa et al.

ICAO specifies performance requirements for navigation services in the aviation industry. These requirements are defined as Navigation Service Levels APV-I, APV-II, and CAT-I. Approach Procedures with Vertical Guidance (APV) are instrument approach Navigation Service Levels that use horizontal (LNAV) and vertical (VNAV) navigation guidance but they do not meet the requirements for precision approach and landing operations. APV is also referred to as LPV (Localizer Performance with Vertical Guidance). An APV approach uses lateral guidance from SBAS and vertical guidance provided by either the barometric altimeter, GBAS or SBAS. In North America, an APV approach enables descent to 60 to 75 m (200 to 250 ft) above the runway, and can only be flown with a WAAS-enabled receiver certified by the US Federal Aviation Authority (FAA).

Two types of APV are specified: APV-I and APV-II. APV-II has stricter requirements, such as 8 m vertical accuracy 95% of the time, compared with 20 m accuracy for APV-I. SBAS using geostationary satellites permit equipment users to fly APV approaches based on the procedure and design criteria published by the ICAO Obstacle Clearance Panel. Category I (CAT-I) is a precision approach Navigation Service Level for the final approach phase of flight with higher requirements for accuracy, integrity, availability, and continuity than APV-I and APV-II. The vertical accuracy in this category is between 4 and 6 m. Presently, in Europe the Instrument Landing System (ILS) Category I approach is the only certified navigation system that supports CAT-I processes.

An extension of the Standard and Recommended Practices (SARPs) to enable use of ground-based augmentation systems (GBAS) to support operations to CAT-II/III minima also exists. CAT-I is a precision instrument approach and landing with a decision height not lower than 60 m (200 ft) above touchdown zone elevation and with either a visibility not less than 800 m (2,265 ft) or a runway visual range not less than 550 m (1,804 ft). CAT-II is as CAT-I, with a decision height lower than 60 m (200 ft) but not lower than 30 m (100 ft), and a runway visual range not less than 350 m (1,148 ft). CAT-IIIA is a precision instrument approach and landing that stipulates a decision height lower than 30 m (100 ft) or no decision height, and a runway visual range not less than 200 m (656 ft). CAT-IIIB – GBAS Approach Service Type D (GAST-D) – specifies a decision height of lower than 15 m (50 ft) or no decision height above touchdown elevation, and a runway visual range less than 200 m (656 ft) but not less than 75 m (246 ft). Autopilot is used until taxi-speed. In the USA, FAA criteria for CAT-IIIB runway visual range allows readings as low as 46 m (150 ft). CAT-IIIC does not specify a decision height or any runway visual limitations. This category is not yet in operation anywhere in the world, as it requires guidance to taxi in conditions of zero visibility. Category IIIB is currently the best available system.

An APV approach with a 200-foot decision height is sometimes called an APV200 (or LPV200) approach. In general, the location equipage aboard an aircraft for APV200 approach has to satisfy very stringent requirements of accuracy, reliability and availability. Of these, reliability is the most important consideration, and this is achieved by creating a very reliable hardware and software solution. The combined hardware and software reliability has to be such that erroneous results occur with a probability less than 10Exp-7 at 100% confidence level during approach and departure. The Minimum Aviation System Performance Standards (MASPS) for GPS Local Area Augmentation System Airborne (LAAS) Equipment (RTCA Do-253C) stipulates several additional integrity requirements or augmentations. These include position solutions with a variety


of smoothing time constants – e.g., dual ionospheric gradient monitoring (DSIGM) – fault detection before and during new satellite additions, satellite geometry scrutiny, and optional onboard autonomous integrity monitoring (Bestmann et al., 2010a, 2010b).

Figure 2 Automatic dependent surveillance system

In the context of ADS-B, which is depicted in Figure 2, several parameters have been defined by the standards community. These define distinct location performance levels for ADS-B, including navigation accuracy category for position (NAC-P) and navigation integrity category (NIC), each with 11 sub-categories; and surveillance integrity level (SIL), which is the probability of containment associated with NIC (Xi et al., 2009; Mohleji and Wang, 2010; ICAO, 2012, 2013; FAA, 2010, 2011; Air Services Australia, 2012; RTCA, 2002, 2006). See Table 5. ADS-B is a cooperative surveillance system which uses a data communication protocol with automatic broadcast of identification, position, velocity, and other pertinent parameters by participating users. Equipment capable of receiving the data can use the data for a variety of applications ranging from situational awareness to aircraft separation management. Table 5 lists the ADS-B navigation accuracy and integrity categories, NAC-P and NIC, and their respective performance requirements. The estimated position uncertainty (EPU) is a 95% accuracy of the position fix, and the containment radius (CR) is a bound on the position error associated with the integrity level represented by SIL. SIL levels range from zero to three, representing unknown integrity levels 10Exp-3, 10Exp-5, and 10Exp-7, respectively. The entries in Table 5 emanate from RTCA Do-260A (RTCA, 2006), with the exception of NIC 6b, which is an unreal category expressive of the containment need specific to the ATLAS programme.

Table 6 indicates both published and draft location performance requirements expressed in terms of ADS-B categories for various applications ranging from radar-like surveillance in non-radar airspace (NRA) to better-than-radar performance for radar

190 A. Musa et al.

airspace applications (RAD), including parallel approach, Final Approach and Runway Occupancy Awareness (FAROA), and surface applications such as Airport Surface Situational Awareness (ASSA). It is to be noticed that most of the applications require a SIL level of 2 (or better), which corresponds to containment integrity of 10Exp-5 per hour; existing certified RAIM algorithms provide 10Exp-7 per hour, corresponding to a SIL level of 3 (Harris and Murphy, 2008). Table 5 ADS-B accuracy and integrity categories together with related performance

requirements

95% horizontal and vertical accuracy bounds (EPU and VEPU)

Horizontal and vertical containment bounds NAC-P

EPU VEPU

NIC

CR VCR 0 = 18.52 km 0 = 37.04 km 1 < 18.52 km 1 < 37.04 km 2 < 7.408 km 2 < 14.816 km 3 < 3.704 km 3 < 7.408 km 4 < 1,852 m 4 < 3.704 km 5 < 926 m 5 < 1,852 m 6 < 555.6 m 6 < 1,111.2 m 6b < 555.6 m 6b < 926 m 7 < 185.2 m 7 < 370.4 m 8 < 92.6 m 8 < 185.2 m 9 < 30 m < 45 m 9 < 75 m < 112 m 10 < 10 m < 15 m 10 < 25 m < 37.5 m 11 < 3 m < 4 m 11 < 7.5 m < 11 m

Note: 1 nautical mile (nm) = 1,852 metres (m).

Table 6 Application-dependent ADS-B accuracy and integrity requirements

Application NAC-P NIC SIL NRA (9.26 km) Do-303 5 4 2 NRA (5.56 km) Do-303 6 5 2 NRA CASCADE Do-260A 5 4 3 NRA CASCADE Do-260 5 5 3 NRA ATLAS Australia 0 6b 2 NRA NPRM FAA 9 7 2 NPRM Comment Boeing 8 6 2 RAD en route (9.26 km) Draft 7 5 3 RAD Terminal (5.56 km) Draft 8 6 3 RAD dep. par. appr. (4.63 km) Draft 8 7 3 RAD ind. par. appr. Draft 8 7 3 En route vis. sep. appr. RFG draft 6 6 1 ASSA/FAROA Surface Draft 9 0 0 In trail procedures RFG Do-312 5 5 2


3.3 Location requirements in marine navigation

Figure 3 lists the major marine navigation phases and application scenarios and Table 7 depicts the marine location and navigation requirements. However, not all the current requirements are shown in Table 7. The stricter requirements emanate from safety of navigation in inland waterways, where a two-dimensional accuracy of 2 to 5 m is normally needed at the 95% confidence level (two-sigma). For harbour approach and entrance, the required accuracy is normally 8 to 20 m (95% confidence level). On the high seas the accuracy requirements are less severe, but the need to avoid protected or endangered marine areas and dangerous weather and sea conditions (wrecks, rocks, and reefs for Scuba diving and fishing) demands accuracies of the order of 100 m. Horizontal positional accuracies of 1 to 100 m (at 95% confidence level) are needed for resource exploration and search and rescue operations in coastal waters. Table 7 Marine location and navigation data requirements

Requirements Accuracy (m)

Availability (%)

Fix interval (seconds)

Fix dimensions

Inland waterways

All ships and tow boats 2–5 99.9 1–2 2

Recreational boats and smaller vessels 5–10 99.9 5–10 2

River engineering and construction vessels 0.1–5 * 99.0 1–2 3

Harbour entrance and approach

Large ships and tow boats 10–20† 99.7 6–10 2

Smaller ships 5–20 99.9 † 2

Resource exploration 1–5 99.0 1 2

Engineering and construction vessels 0.1–5* 99.0 1–2 2 and 3

Fishing, recreational and other small vessels 8–20 99.7 † 2

Coastal navigation

All ships and tows 460 99.7 120 2

Recreational boats and smaller vessels 460–3,700 99.0 300 2

Commercial fishing 460 99.0 60 2

Resource exploration 1.0–100 99.0 1 2

Search operations and border enforcement 460 99.7 60 2

Recreational fishing 460 99.0 300 2

Ocean navigation

All ships 1,800–3,700 99.0‡ ¶ 2

Large ships 185–460 99.0 300 2

Resource exploration 10–100 99.0 60 2

Search and rescue operations 185–460 99.0 60 2

Notes: *Vertical dimension; †harbour dependent; ‡at least every 12 hours; ¶ 15 minutes minimum or as desired, 2 hours maximum.

192 A. Musa et al.

Figure 3 Marine navigation application scenarios

All these requirements are met by differential GPS (DGPS), which normally provides a two-dimensional error of 1 to 3 m, greatly enhancing harbour entrance and navigation. Marine DGPS currently supports a wide range of public, private and military needs, ranging from hydrographic surveying, rig installation and functions, vessel traffic management services, search and rescue operations, environmental assessment and clean-up operations, to underwater mine detection and disposal. For example, the US Coast Guard Maritime DGPS Service broadcasts correction signals on marine radio-beacon frequencies to improve the accuracy and integrity of GPS-derived positions. The service provides 10 m accuracy (at 95% confidence level), together with integrity alarms for GPS and DGPS out-of-tolerance conditions within 10 seconds of detection. The service availability is 99.7% per month.

As a result of the success of DGPS and budgetary constraints, the US Coast Guard terminated the transmission of Loran-C signals in February 2010, but an enhanced Loran system (eLoran) is currently in operation in, e.g., UK, operated by VT Communication on behalf of the General Light House Authorities of the UK and Ireland. eLoran is independent of, dissimilar to, and complements GNSS. It meets the accuracy, availability, integrity, and continuity performance required for aviation, non-precision instrument approaches, maritime harbour entrance and approach, and many aspects of location-based services (LBS). It is also a precise source of frequency for many applications, including telecommunications. A GPS jamming test conducted by the General Light House Authorities of the UK and Ireland in 2009 (Basker et al., 2010; Bartone, 2008) concluded that the denial of GPS and DGPS services has a significant impact on maritime safety. eLoran was unaffected by GPS jamming and achieved an accuracy of 8.1 m (95% confidence level), which is comparable to standalone, single-frequency GPS.


3.4 Indoor requirements

The provision of navigation and guidance services in challenging indoor environments (in manufacturing complexes, large office buildings, shopping centres, warehouses, railway stations, airports, hospitals, sport arenas, etc.) is very important. In the case of emergency services (e.g., to locate first responders in a rescue situation inside a building), obtaining reliable location is particularly very challenging and superior location accuracies and reliabilities are required than in outdoor environments. The panellists agreed that most applications of indoor positioning demand that a user can be located in a certain room inside the building. As a consequence, the required location accuracy depends on the typical room size in the application domain. For example, in the case of a shopping complex, an accuracy of better than 3 m for location determination in the two-dimensional horizontal plane is necessary. In addition, the system must be able to locate the user on the correct floor in a multi-storey building. The accuracy requirement in height, therefore, depends on the ceiling height of the building: typically, the required accuracy would be better than 2.5 m for modern office buildings.

The most stringent accuracy requirements in indoor logistics are found in some manufacturing shop-floors and in scientific research laboratories. In complex manufacturing scheduling processes, such as in semiconductor fabrication labs (Thiesse and Fleisch, 2008), the needed positional accuracy may exceed 10 cm in the horizontal plane (Baker, 1998; Kuo and Huang, 2006; Dabbas and Fowler, 2003). There is a large number of activities and movements of parts that take place in a typical semiconductor lab and there is complexity in providing location information for process automation in those facilities.

4 Location technologies and methods for logistics

Having determined the requirements for location data for logistics in the foregoing sections, in the present section we chart, through a second round of extensive literature review, the array of positioning technologies that can deliver the needs. As mentioned earlier, location technologies for logistics can be categorised according to the environment (indoors or outdoors) in which they are most suitable. However, many of the methods are usually combined through hybridisation of sensors in the two environments of indoor and outdoor. Table 8 presents the many methods that are at the core of location for logistics applications indoors and outdoors. Figure 4 depicts the system architecture of assisted-GPS. Some of the older and waning methods have not been included in the table simply because their future is greatly diminished.

The use of high-sensitivity GNSS (HS-GNSS) receivers is not included in Table 8. HS-GNSS receivers acquire and track weak signals by lowering the threshold of useful signal-to-noise ratio, whereby the sensitivity can be increased by as much as 15 dB compared with a conventional receiver. Signal availability thus increases by using a HS-GNSS receiver, but nonetheless the corresponding noise and errors are also inadvertently magnified (Ziedan, 2006). Furthermore, a HS-GNSS receiver requires more accurate time reference and is likely to consume slightly more power during acquisition than equivalent non-HS-GNSS receiver. HS-GNSS for indoor applications, whilst still important and attractive, seems to be giving way to the use of radio signals from

194 A. Musa et al.

preinstalled infrastructure (like WiFi, UWB, RFID, IMES), and use of digital map databases of interiors. For example, in the UK there are some small enterprises that specialise in gathering precise databases of interiors of public and private buildings for emergency needs by first responders. Table 8 Taxonomy of modern location technologies with logistics potential

Tech

nolo

gy

Indo

or

appl

icab

ility

O

utdo

or

appl

icab

ility

R

elat

ive

mer

its

Rel

ativ

e de

mer

its

Typi

cal i

ndoo

r an

d ou

tdoo

r ac

cura

cy (9

5%)

GN

SS-b

ased

met

hods

Pure

, una

ided

GN

SS

App

licab

le b

ut th

e ou

tcom

e is

usu

ally

un

relia

ble.

App

licab

le.

Free

and

ava

ilabl

e

alm

ost e

very

whe

re, e

xcep

t in

door

s an

d un

derg

roun

d.

Sign

als

cann

ot p

enet

rate

mos

t bui

ldin

gs w

ith

suff

icie

nt s

tren

gth

for t

he re

ceiv

er to

dec

ode

the

navi

gatio

n m

essa

ge. S

ever

e m

ultip

ath

effe

cts

occu

r ind

oors

and

in u

rban

are

as.

Tre

e ca

nopi

es c

an im

pair

sig

nal r

ecep

tion.

30 to

100

m, d

epen

ding

on

obse

rvat

ion

mod

e. P

PP c

an

do m

uch

bette

r, yi

eldi

ng

cent

imet

re a

ccur

acy.

Lan

d-ba

sed

DG

NSS

A

pplic

able

if

rece

iver

can

als

o de

code

GN

SS

sign

als.

App

licab

le.

Incr

ease

s av

aila

bilit

y an

d ac

cura

cy. C

orre

ctio

ns c

an

be s

ent b

y m

any

mea

ns:

mar

ine

radi

o-be

acon

s,

VH

F an

d U

HF

data

link

s,

cell

phon

e ne

twor

ks, r

adio

an

d te

levi

sion

bro

adca

sts,

in

tern

et, a

nd L

oran

sig

nals

.

Req

uire

s pr

eins

talle

d, c

ostly

gro

und-

base

d in

fras

truc

ture

. May

nee

d a

netw

ork

conn

ectio

n an

d su

bscr

iptio

n. T

rack

ing

and

mul

tipat

h er

rors

are

unc

orre

late

d be

twee

n re

fere

nce

and

user

sta

tions

.

1 m

, dep

endi

ng o

n th

e as

sist

ance

dat

a. N

RT

K

achi

eves

bet

ter t

han

5 cm

w

here

refe

renc

e st

atio

ns a

re

dens

e an

d co

rrec

tion

late

ncy

is

low

.

SBA

S an

d si

mila

r A

pplic

able

if

rece

iver

can

als

o de

code

GN

SS

sign

als.

App

licab

le.

Prov

ides

dif

fere

ntia

l co

rrec

tions

and

inte

grity

in

form

atio

n at

aff

orda

ble

cost

(Pra

sad

and

Rug

gier

i, 20

05).

Nor

mal

ly c

over

s a

wid

e ar

ea.

Req

uire

s co

stly

pre

inst

alle

d, s

pace

-bas

ed

and

grou

nd-b

ased

infr

astr

uctu

re. S

igna

l D

oppl

er c

ollis

ions

are

like

ly d

ue to

low

dy

nam

ics

of S

BA

S sa

telli

tes.

Im

prov

ed

ephe

mer

is a

nd c

lock

dat

a br

oadc

asts

by

GN

SS s

atel

lites

them

selv

es p

lus

dual

fr

eque

ncy

iono

sphe

re c

orre

ctio

n fo

r civ

il us

ers

coul

d lim

it th

e be

nefi

ts o

f wid

e-ar

ea

diff

eren

tial G

NSS

.

1 m

AG

PS

App

licab

le.

App

licab

le.

Incr

ease

s av

aila

bilit

y

and

accu

racy

. Red

uces

T

TFF

. Can

als

o se

nd

othe

r ass

ista

nce

data

su

ch a

s na

viga

tion

m

odel

s, re

fere

nce

loca

tion,

fr

eque

ncy,

and

tim

e

(van

Dig

gele

n, 2

009)

.

Nee

ds n

etw

ork

conn

ectio

n, a

nd th

ere

are

priv

acy

conc

erns

. TT

FF is

not

alw

ays

optim

al s

ince

the

navi

gatio

n m

essa

ge ti

me

mar

k m

ust s

till b

e de

code

d.

20 m

, dep

endi

ng o

n th

e as

sist

ance

dat

a (F

igur

e 4)

.

BG

PS

A

pplic

able

. A

llow

s th

e us

e of

sig

nal

snap

shot

s in

mob

ile

term

inal

s w

ithou

t ne

twor

k co

nnec

tion.

Po

sitio

ns c

an b

e ca

lcul

ated

in

stan

tane

ousl

y, w

ithin

fr

actio

ns o

f a s

econ

d (P

etro

vski

et a

l., 2

008)

.

Doe

s no

t hav

e th

e ad

vant

age

of A

GPS

in

resp

ect o

f fre

quen

cy a

ssis

tanc

e to

con

stra

in

fron

tend

clo

ck d

rift

, whi

ch e

nabl

es lo

nger

in

tegr

atio

n pe

riod

s fo

r in

door

pos

ition

ing.

R

equi

res

inde

pend

ently

pre

dict

ed e

phem

eris

.

20 m

, but

can

be

impr

oved

su

bsta

ntia

lly in

PPP

mod

e.

SAG

PS

A

pplic

able

. R

educ

ed T

TFF

in s

igna

l-ch

alle

nged

env

iron

men

ts

is th

e ch

ief b

enef

it, b

ut

accu

racy

gai

ns m

ay a

lso

resu

lt (M

atto

s, 2

008)

.

Deg

rade

d ac

cura

cy a

fter

abo

ut th

ree

days

of

pred

icte

d ep

hem

eris

. Req

uire

s at

leas

t 30

0/40

0 M

Hz

CPU

.

Bet

ter

than

20

m fo

r ep

hem

eris

pre

dict

ion

age

less

th

an 2

4 ho

urs.


Table 8 Taxonomy of modern location technologies with logistics potential (continued)

Tech

nolo

gy

Indo

or

appl

icab

ility

O

utdo

or

appl

icab

ility

Re

lativ

e m

erits

Re

lativ

e de

mer

its

Typi

cal i

ndoo

r and

out

door

ac

cura

cy (9

5%)

Dea

d re

ckon

ing

(see

not

e 1)

Odo

met

ry

App

licab

le b

ut,

beca

use

of it

s po

or a

ccur

acy,

it

is ra

rely

use

d in

door

s.

App

licab

le,

ofte

n in

tegr

ated

on

veh

icle

s by

auto

mak

ers.

Val

uabl

e as

whe

el

spee

d se

nsor

s (W

SS),

fo

r ant

ilock

bra

ke sy

stem

(A

BS)

, and

for i

nteg

ratio

n w

ith G

NSS

on

auto

mot

ives

.

Low

-cos

t pas

sive

odo

met

ers p

erfo

rm p

oorly

at

low

spee

ds (s

o ca

lled

dead

band

, nor

mal

ly

2 to

5 k

m p

er h

our)

. Act

ive

sens

ors,

base

d on

the

Hal

l effe

ct, g

ive

suffi

cien

tly st

rong

si

gnal

s at a

ll sp

eeds

but

are

exp

ensi

ve.

Opt

ical

sens

ors a

re v

ulne

rabl

e to

dirt

. M

eani

ngfu

l mod

ern

appl

icat

ions

requ

ire

inte

grat

ion

with

, e.g

., G

NSS

.

50 m

whe

n in

tegr

ated

with

G

NSS

. The

dom

inan

t err

or

sour

ce is

scal

e fa

ctor

err

ors d

ue

to u

ncer

tain

ty in

whe

el ra

dii.

Pede

stria

n de

ad

reck

onin

g A

pplic

able

but

m

ore

rese

arch

is

nee

ded

for

accu

raci

es o

f 1%

to

2%

.

App

licab

le b

ut

see

dem

erits

. U

sefu

l for

ped

estri

an

pers

onne

l mon

itorin

g, a

nd

for t

he m

ilita

ry a

nd fi

rst

resp

onde

rs.

Und

er c

lear

skie

s, G

NSS

pro

vide

s de

cim

etre

acc

urac

y. F

or p

edes

trian

na

viga

tion

in G

NSS

sign

al-c

halle

nged

en

viro

nmen

ts, p

edes

trian

mec

hani

satio

n m

ust b

e co

nsid

ered

. Err

ors d

epen

d on

pe

dest

rian

mov

emen

t cha

ract

eris

tics.

Enor

mou

s cha

lleng

es (i

nclu

ding

sens

or

mou

ntin

g an

d le

ver-

arm

dis

tanc

e) re

mai

n to

be

ove

rcom

e fo

r err

ors t

o be

less

than

1%

.

1% to

2%

of d

ista

nce

trave

lled.

Stan

dalo

ne IN

S In

door

ap

plic

atio

ns a

re

clea

rly li

mite

d be

caus

e of

the

unde

rlyin

g pr

inci

ples

.

App

licab

le

but a

dequ

ate

calib

ratio

n is

ne

eded

.

MEM

S-ba

sed

IMU

sy

stem

s hav

e w

ides

prea

d ap

plic

atio

ns, r

angi

ng fr

om

pede

stria

n na

viga

tion,

in

-car

nav

igat

ion,

bal

listic

m

issi

le g

uida

nce,

to sp

ace

appl

icat

ions

. The

y ha

ve

smal

l foo

tprin

t, lo

w

wei

ght,

and

are

pow

er

effic

ient

. Con

sum

er-g

rade

IM

Us a

re in

expe

nsiv

e bu

t ha

ve p

oor e

rror

char

acte

ristic

s.

Sens

or b

iase

s are

the

dom

inan

t sou

rce

of

erro

r. Th

ey h

ave

larg

e ra

ndom

wal

ks a

nd

vibr

atio

n re

ctifi

catio

n er

rors

. Sen

sors

are

al

so te

mpe

ratu

re se

nsiti

ve. A

slow

ly v

aryi

ng

bias

can

not b

e ca

libra

ted

prio

r to

field

de

ploy

men

t. 3

D g

yros

are

nee

ded

to

over

com

e m

ount

ing

prob

lem

s, bu

t thi

s in

crea

ses c

ost.

In g

ener

al, c

ost r

emai

ns a

co

ncer

n in

nav

igat

ion-

grad

e IN

S.

For n

avig

atio

n-gr

ade

IMU

, po

sitio

n er

ror i

s les

s tha

n

4 km

/h, g

yro

erro

r 0.0

15 d

eg/h

, ac

cele

rom

eter

err

or

0.1

mill

igal

.

196 A. Musa et al.


Tech

nolo

gy

Indo

or

appl

icab

ility

O

utdo

or

appl

icab

ility

R

elat

ive

mer

its

Rel

ativ

e de

mer

its

Typi

cal i

ndoo

r an

d ou

tdoo

r ac

cura

cy (

95%

)

Fea

ture

mat

chin

g (F

EM

A)

(see

not

e 2)

Map

mat

chin

g (M

AM

A)

App

licab

le

but h

eigh

ts a

re

diff

icul

t with

out

3D m

odel

s of

bu

ildin

gs.

App

licab

le.

MA

MA

is n

ow a

key

fe

atur

e of

alm

ost a

ll la

nd

and

auto

nom

ous

vehi

cle

navi

gatio

n sy

stem

s.

FEM

A a

lso

has

seve

ral

appl

icat

ions

in a

vion

ics.

P

edes

tria

n na

viga

tion

in

urba

n ar

eas

is a

lso

a be

nefi

ciar

y. F

EM

A c

an

also

be

used

to d

eter

min

e a

prio

ri w

hat t

he e

ffec

ts o

f bu

ildin

gs w

ill b

e on

GN

SS

sign

als.

MA

MA

can

not c

ope

with

inst

ance

s in

w

hich

the

vehi

cle

is n

ot o

n th

e ro

ad, e

.g.,

whe

n pa

rkin

g or

on

new

and

unm

appe

d ro

ad. W

hen

the

vehi

cle

is o

n a

unid

irec

tion

al

mul

ti-la

ne r

oad,

MA

MA

can

not i

dent

ify

the

righ

t lan

e.

20 m

but

can

be

redu

ced

to

10 m

with

acc

urat

e m

ap

data

base

s.

Poin

t rec

ogni

tion

wit

hout

pre

inst

alle

d be

acon

s

App

licab

le.

App

licab

le.

Lea

ds to

uni

que

loca

tion

s by

pro

xim

ity

if th

e be

acon

s (r

efer

ence

poi

nts

or

obje

cts)

are

vis

ibly

dis

tinct

fr

om n

eigh

bour

hood

ob

ject

s an

d if

onb

oard

C

PU

ove

rhea

ds c

an b

e ac

com

mod

ated

.

Nee

ds p

edom

eter

s, a

ccel

erom

eter

s, g

yros

, m

agne

tom

eter

s fo

r m

easu

ring

trav

elle

d di

stan

ce a

nd h

eadi

ng. I

t is

not a

lway

s po

ssib

le to

fin

d un

ique

pos

ition

s, e

spec

iall

y if

thos

e po

sitio

ns a

re n

ot s

uita

bly

dist

inct

fr

om n

eigh

bour

ing

poin

ts. S

enso

rs m

ay b

e su

bjec

t to

low

vis

ibili

ty. I

ndoo

rs, f

urni

ture

an

d ot

her

item

s m

ay o

bstr

uct p

ositi

ons.

P

artic

le f

ilter

s m

ay b

e re

quir

ed to

arr

ive

at

opt

imal

sol

utio

ns a

nd th

ese

are

com

puta

tiona

lly in

tens

ive.

In p

rinc

iple

, the

re is

no

limit

to

accu

racy

if th

e ex

act l

ocat

ions

of

the

beac

ons

can

be f

ound

.

Loca

l rad

io n

avig

atio

n (s

ee n

ote

3)

Mob

ile te

leph

ony

netw

orks

. The

re

are

man

y te

chni

ques

in

this

cat

egor

y

(see

not

e 4)

App

licab

le.

App

licab

le.

Net

wor

k re

sour

ces

alre

ady

exis

t and

no

addi

tiona

l in

vest

men

t may

be

nece

ssar

y on

the

part

of

the

user

.

The

rel

ativ

ely

poor

acc

urac

y of

all

the

met

hods

in th

is c

ateg

ory

lim

its th

e us

e

of th

ese

tech

niqu

es in

inte

grat

ed n

avig

atio

n sy

stem

s. F

utur

e G

NSS

met

hods

may

m

ake

cellu

lar

met

hods

less

attr

activ

e. I

n la

rge-

scal

e em

erge

ncie

s, c

ellu

lar

reso

urce

s m

ay b

e co

mpr

omis

ed b

y di

sast

er o

r ov

erw

helm

ed b

y de

man

d.

50 to

200

m, d

epen

ding

on

the

met

hod

used

and

mea

sure

men

t co

nditi

ons.

Shor

t-ra

nge

wir

eles

s ne

twor

ks. S

ee n

ote

5 fo

r th

e m

any

sign

al

type

s av

aila

ble

for

this

met

hod

App

licab

le.

App

licab

le.

The

se s

omet

imes

use

ex

istin

g in

fras

truc

ture

(e

spec

iall

y in

the

case

of

WiF

i) a

nd s

o ar

e re

lativ

ely

chea

p w

here

su

ch in

fras

truc

ture

exi

sts.

In

man

y ap

plic

atio

ns,

how

ever

, the

infr

astr

uctu

re

has

to b

e sp

ecia

lly

esta

blis

hed

(Čap

kun

and

Hub

aux,

200

6; B

ensk

y,

2008

; Ret

sche

r, 2

006,

20

07; R

etsc

her

et a

l.,

2007

).

Pre

inst

alle

d in

fras

truc

ture

is n

eces

sary

, or

(in

the

case

of

ad h

oc n

etw

orks

) m

ust b

e es

tabl

ishe

d du

ring

the

surv

ey. M

ulti

path

and

lim

ited

pene

trat

ion

capa

bilit

y of

the

sign

als

can

be a

hin

dran

ce in

door

s. F

or o

utdo

or

appl

icat

ions

, a la

rge

num

ber

of n

etw

ork

node

s is

oft

en n

eces

sary

.

Shor

t-ra

nge

beac

ons

and

UW

B

can

give

sub

-met

re a

ccur

acie

s.

By

usin

g fi

nger

prin

ting

and

RS

S, W

iFi c

an y

ield

1 to

5 m

ac

cura

cy (

Win

and

Sch

oltz

, 19

98).



Tech

nolo

gy

Indo

or

appl

icab

ility

O

utdo

or

appl

icab

ility

Re

lativ

e m

erits

Re

lativ

e de

mer

its

Typi

cal i

ndoo

r an

d ou

tdoo

r ac

cura

cy (9

5%)

Loca

l rad

io n

avig

atio

n (s

ee n

ote

3)

TV a

nd F

M s

igna

ls

(see

not

e 6)

A

pplic

able

. A

pplic

able

. Th

ese

use

exis

ting

infr

astru

ctur

e at

rela

tivel

y ch

eap

cost

. Car

rier-

phas

e po

sitio

ning

is p

ossi

ble

w

ith a

ny ra

dio

sign

al.

TV s

igna

ls h

ave

larg

e po

wer

, low

er fr

eque

ncy

(54

to 8

00 M

Hz)

, hig

h fr

eque

ncy

dive

rsity

, and

lo

wer

gra

zing

ang

le

(hen

ce le

ss a

ttenu

atio

n).

Posi

tioni

ng a

ccur

acy

has

not i

mpr

oved

, du

e to

(am

ong

othe

r rea

sons

) mul

tipat

hing

an

d di

ffic

ultie

s in

err

or m

odel

ling.

In

man

y ci

ties,

par

ticul

arly

in E

urop

e, th

e tra

nsm

itter

s fo

r diff

eren

t net

wor

ks a

re o

ften

all l

ocat

ed a

t the

sam

e si

te, t

here

by li

miti

ng

geog

raph

ic s

prea

d an

d si

gnal

geo

met

ry.

5 to

20

m, d

epen

ding

on

how

se

rious

mul

tipat

h ef

fect

s ar

e.

Pseu

dolit

es.

Thes

e ar

e gr

ound

tra

nsce

iver

s th

at

trans

mit

and

rece

ive

GPS

-like

sig

nals

App

licab

le.

App

licab

le.

GPS

rece

iver

s ca

n re

ceiv

e an

d de

code

pse

udol

ite

sign

als,

just

like

pse

udol

ite

rece

iver

s ca

n re

ceiv

e an

d de

code

GPS

sig

nals

. In

crea

ses

avai

labi

lity,

ac

cura

cy a

nd in

tegr

ity

both

indo

ors

and

outd

oors

. U

sed

in n

iche

mar

kets

, e.

g., p

reci

sion

app

roac

h an

d la

ndin

g of

airc

rafts

.

Pseu

dolit

e’s

use

of a

C/A

cod

e-lik

e si

gnal

m

eans

that

the

rece

ived

pse

udol

ite s

igna

l ca

n be

mor

e th

an 2

0 dB

stro

nger

than

the

GPS

C/A

-cod

e, th

us le

adin

g to

inte

rfer

ence

. Pu

lsin

g th

e ps

eudo

lite

sign

al c

an h

elp.

H

ardw

are

cost

can

be

high

(tho

usan

ds

of d

olla

rs).

Pseu

dolit

es a

re n

ot ti

me

sync

hron

ised

with

GN

SS o

r with

in th

e sy

stem

itse

lf, m

akin

g di

ffer

entia

l ope

ratio

ns

nece

ssar

y. A

ttem

pts

to s

ynch

roni

se

pseu

dolit

es h

ave

led

to la

rger

pos

ition

ing

erro

rs.

In d

iffer

entia

l mod

e, c

entim

etre

le

vel a

ccur

acie

s ar

e po

ssib

le.

Loca

talit

es

App

licab

le.

App

licab

le.

This

is a

ctua

lly a

noth

er

type

of p

seud

olite

, bu

t sol

ves

mos

t of t

he

diff

icul

ties

of c

onve

ntio

nal

pseu

dolit

e. C

an tr

ack

both

lo

cata

lite

and

GPS

sig

nals

, th

us a

llow

ing

seam

less

fu

nctio

nalit

y. H

ighl

y

time-

sync

hron

ised

w

ithou

t ato

mic

clo

cks,

th

us e

nabl

ing

prec

ise

sing

le-p

oint

pos

ition

ing.

Sc

alab

le: c

an b

e us

ed fo

r sm

all a

nd w

ide

area

ap

plic

atio

ns. C

ost

effe

ctiv

e. H

igh

relia

bilit

y.

Can

be

used

to b

uild

ad

hoc

net

wor

ks fo

r em

erge

ncy

oper

atio

ns.

The

tech

nolo

gy is

pat

ente

d by

Loc

ata

Cor

pora

tion

of C

anbe

rra

(Bar

nes

et a

l.,

2003

; Mar

tin e

t al.,

200

7) a

nd d

evel

opm

ent

effo

rts s

eem

to h

ave

wan

ed in

rece

nt ti

mes

. H

ow a

nd th

e ex

tent

to w

hich

loca

talit

es

sign

als

avoi

d or

redu

ce in

terf

eren

ce w

ith

GN

SS h

as n

ot b

een

inve

stig

ated

out

side

of

Loc

ata

Cor

pora

tion.

As

in c

onve

ntio

nal

pseu

dolit

es, i

ssue

s re

mai

n, in

clud

ing

tropo

sphe

ric e

rror

mod

ellin

g, in

door

sig

nal

pene

tratio

n de

lays

, sel

ectio

n of

opt

imal

fr

eque

ncie

s an

d be

st ra

ngin

g si

gnal

st

ruct

ures

, and

inte

grat

ion

with

INS

an

d im

agin

g se

nsor

s.

Sub-

cent

imet

re a

ccur

acy

is

poss

ible

in b

oth

diff

eren

tial a

nd

non-

diff

eren

tial m

odes

, ind

oors

an

d ou

tdoo

rs.

198 A. Musa et al.


Tech

nolo

gy

Indo

or

appl

icab

ility

O

utdo

or

appl

icab

ility

R

elat

ive

mer

its

Rel

ativ

e de

mer

its

Typi

cal i

ndoo

r an

d ou

tdoo

r ac

cura

cy (9

5%)

Loca

l rad

io n

avig

atio

n (s

ee n

ote

3)

Indo

or m

essa

ging

sy

stem

(IM

ES)

from

Ja

pan

Aer

ospa

ce

Exp

lora

tion

Age

ncy

App

licab

le.

App

licab

le

whe

re th

ere

ar

e IM

ES

tran

smitt

ers.

L

imite

d ra

nge.

Low

pow

er c

onsu

mpt

ion,

lo

w tr

ansm

itter

cos

t, an

d av

aila

bilit

y bo

th in

door

s an

d ou

tdoo

rs (

Man

andh

ar

et a

l., 2

008)

.

Pote

ntia

l for

inte

rfer

ence

with

GN

SS

sign

als

(see

the

desc

ript

ion

of I

ME

S in

the

App

endi

x), a

lthou

gh n

ew G

PS s

igna

ls s

uch

as L

2C c

an d

imin

ish

the

risk

. The

cos

t of t

he

need

ed p

rein

stal

led

infr

astr

uctu

re c

an b

e hi

gh.

10 m

POSC

OM

M

(pos

ition

ing

and

com

mun

icat

ions

sy

stem

fro

m

NA

VSY

S C

orpo

ratio

n,

Col

orad

o Sp

ring

s,

CO

.)

App

licab

le.

App

licab

le.

POSC

OM

M’s

sof

twar

e-de

fine

d ra

dios

(SD

Rs)

are

co

nfig

ured

to o

pera

te a

s bo

th G

PS r

ecei

ver

and

a 90

0 M

Hz

tran

scei

ver.

T

he p

ositi

onin

g

serv

ice

leve

rage

s bo

th

GPS

-der

ived

pse

udor

ange

s an

d ca

rrie

r-ph

ase

obse

rvat

ions

toge

ther

w

ith th

e co

mm

unic

atio

ns

chan

nel’

s T

OA

m

easu

rem

ents

. The

sys

tem

is

bas

ed o

n lo

w-c

ost,

of

f-th

e-sh

elf h

ardw

are

and

soft

war

e. F

or m

axim

um

flex

ibili

ty, t

he m

ultip

le

mas

ter

units

pro

vidi

ng

TO

A a

ssis

tanc

e sh

are

the

avai

labl

e sp

ectr

um u

sing

ei

ther

CM

DA

, TD

MA

, or

FDM

A. T

he a

ssoc

iate

d vi

deo

cam

era

prov

ides

re

gist

ered

imag

ery

of th

e sc

ene

for

situ

atio

nal

awar

enes

s an

d m

appi

ng.

The

aut

hors

cou

ld n

ot e

stab

lish

the

unit

cost

of

the

prod

uct b

ut b

elie

ve th

at it

is h

igh.

The

co

mm

unic

atio

ns c

hann

el m

ay in

terf

ere

with

th

e G

PS r

ecei

ver

chan

nel,

and

it m

ay b

e im

poss

ible

to c

omm

unic

ate

whi

le tr

acki

ng.

Inte

grat

ion

of a

ME

MS

IMU

ass

ists

in

filte

ring

and

trac

king

of T

OA

mea

sure

men

ts

in e

nvir

onm

ents

with

deg

rade

d G

PS s

igna

ls.

5 m



Tech

nolo

gy

Indo

or

appl

icab

ility

O

utdo

or

appl

icab

ility

Re

lativ

e m

erits

Re

lativ

e de

mer

its

Typi

cal i

ndoo

r and

out

door

ac

cura

cy (9

5%)

Inte

grat

ed n

avig

atio

n G

NSS

+IN

S A

pplic

able

but

in

door

s (w

ithou

t ZU

PT fr

om G

NSS

or

oth

er s

ourc

es)

the

erro

r of I

NS

is

like

ly to

gro

w

quic

kly.

App

licab

le.

This

is s

o fa

r the

m

ost i

mpo

rtant

sen

sor

fusi

on s

trate

gy. G

NSS

m

easu

rem

ents

pre

vent

the

time-

depe

nden

t drif

t of

INS

solu

tions

, whi

le IN

S m

easu

rem

ents

sm

ooth

the

GN

SS s

olut

ion

and

brid

ges

sign

al g

aps.

GN

SS+I

NS

inte

grat

ion

also

mak

es

INS

prac

tical

with

low

er

cost

tact

ical

-gra

de IN

S se

nsor

s (A

bdel

-Ham

id

et a

l., 2

006)

.

The

navi

gatio

n m

odul

e be

com

es m

ore

expe

nsiv

e th

an s

tand

alon

e sy

stem

s. T

he

estim

atio

n pr

oble

ms

beco

me

nonl

inea

r an

d va

rious

var

ietie

s of

ext

ende

d K

alm

an

filte

r and

arti

ficia

l neu

ral n

etw

orks

(G

rejn

er-B

rzez

insk

a et

al.,

200

7; T

hien

elt

et a

l., 2

007)

hav

e to

be

used

for m

any

prac

tical

pro

blem

s, re

quiri

ng p

rem

ium

on

boar

d C

PU a

nd p

rior c

alib

ratio

n.

Nor

mal

ly p

erfo

rms

bette

r tha

n st

anda

lone

sys

tem

s. A

ccur

acy

depe

nds o

n th

e qu

ality

of

GN

SS re

ceiv

er a

nd IN

S se

nsor

, th

e ty

pe o

f int

egra

tion

(loos

e,

tight

, ultr

a-tig

ht a

nd d

eep)

, and

es

timat

ion

met

hods

use

d.

GN

SS+I

NS+

CSA

C

App

licab

le.

App

licab

le.

Prec

ise

time

rem

oves

one

of

the

dom

inan

t sou

rces

of

err

ors

in p

ositi

onin

g by

G

NSS

.

Still

in it

s inf

ancy

and

uni

t cos

t rem

ains

hi

gh.

1 m

or b

ette

r

GN

SS+I

NS+

La

ser s

cann

er

App

licab

le

but c

ost i

s an

im

porta

nt fa

ctor

.

App

licab

le.

The

num

ber o

f au

tom

otiv

es c

arry

ing

lase

r ra

ngef

inde

rs is

incr

easi

ng

and

thes

e ca

n be

exp

loite

d fo

r int

egra

ted

navi

gatio

n.

Lase

rs o

ffer

the

adva

ntag

e of

inst

anta

neou

s 3D

ca

ptur

e w

ithou

t mot

ion

arte

fact

s in

here

nt to

dy

nam

ic s

cann

ing

sens

ors.

Th

e na

scen

t tec

hnol

ogy

of

flash

LiD

AR

(3D

cam

eras

) of

fers

the

poss

ibili

ty o

f in

crea

sing

the

func

tiona

lity

of la

sers

, e.g

., fo

r mob

ile

map

ping

.

The

use

of la

ser s

cann

ers

requ

ires

accu

rate

G

IS d

atab

ase

of th

e ge

ogra

phy.

The

mor

e th

e nu

mbe

r of s

enso

rs in

an

inte

grat

ed

navi

gatio

n so

lutio

n, th

e m

ore

the

com

plex

ity

of th

e es

timat

ion

prob

lem

and

hen

ce th

e gr

eate

r the

nee

d fo

r pre

miu

m o

nboa

rd

proc

esso

rs. T

he in

here

nt h

ardw

are

cost

m

akes

this

tech

niqu

e cu

rren

tly v

iabl

e fo

r on

ly a

dvan

ced

avio

nics

and

tran

spor

tatio

n.

Acc

urac

y de

pend

s on

the

qual

ity o

f the

inte

grat

ed s

enso

rs

and

estim

atio

n al

gorit

hms

used

. O

pera

tiona

l-gra

de la

sers

off

er a

ra

ngin

g ac

cura

cy o

f 2 c

m a

nd

max

imum

rang

ing

dist

ance

of

abou

t 200

m.

200 A. Musa et al.


Tech

nolo

gy

Indo

or

appl

icab

ility

O

utdo

or

appl

icab

ility

Re

lativ

e m

erits

Re

lativ

e de

mer

its

Typi

cal i

ndoo

r and

out

door

ac

cura

cy (9

5%)

Inte

grat

ed n

avig

atio

n

Coo

pera

tive

met

hods

(see

not

e 7)

A

pplic

able

. A

pplic

able

. C

an im

prov

e th

e po

sitio

ning

per

form

ance

fo

r an

entir

e gr

oup

of u

nits

or

per

sonn

el. D

iffer

ent u

nit

mem

bers

may

be

kitte

d w

ith e

quip

men

t of

diffe

ring

soph

istic

atio

n.

Suita

ble

for a

nti-j

amm

ing

stra

tegi

es.

Uni

t cos

t can

be

exor

bita

nt b

ecau

se o

f the

ne

ed fo

r coo

pera

tion

and

for m

ulti-

sens

or

inte

grat

ion.

Dep

ends

on

the

unde

rlyin

g te

chno

logi

es.

Not

es: 1

D

ead

reck

onin

g (D

R) i

s the

pro

cess

of e

stim

atin

g on

e’s c

urre

nt p

ositi

on b

ased

on

a pr

evio

usly

det

erm

ined

pos

ition

, and

adv

anci

ng th

at p

ositi

on b

ased

on,

e.g

.,

spee

d, e

laps

ed ti

me,

and

cou

rse.

2

Feat

ure

mat

chin

g sc

hem

es in

clud

e te

rrai

n-re

fere

nced

nav

igat

ion

(TR

N),

imag

e m

atch

ing

(esp

ecia

lly w

ith L

iDA

R-g

ener

ated

terr

ain

data

base

), m

ap m

atch

ing,

an

d st

ella

r nav

igat

ion.

In g

ener

al, t

hese

tech

niqu

es d

eter

min

e th

e us

er’s

pos

ition

by

mea

surin

g fe

atur

es o

f the

env

ironm

ent (

e.g.

, ter

rain

hei

ghts

or r

oads

) an

d co

mpa

ring

them

with

a d

atab

ase,

sim

ilar t

o th

e m

anne

r tha

t a p

edes

trian

wou

ld c

ompa

re la

ndm

arks

with

a m

ap o

r a m

enta

l pic

ture

of t

he te

rrai

n. F

eatu

re

mat

chin

g sy

stem

s nee

d in

itial

isat

ion

with

an

appr

oxim

ate

posi

tion

so a

s to

dete

rmin

e th

e re

gion

of t

he d

atab

ase

whe

re to

com

men

ce th

e se

arch

. Lim

iting

the

data

base

sear

ch a

rea

natu

rally

redu

ces t

he c

ompu

tatio

nal o

verh

ead

and

the

num

ber o

f ins

tanc

es in

whi

ch th

ere

are

mor

e th

an o

ne m

atch

bet

wee

n th

e m

easu

red

feat

ures

and

thos

e in

the

data

base

. To

be a

ble

to d

eter

min

e th

e re

lativ

e po

sitio

ns o

f the

mea

sure

d fe

atur

es, m

ost i

mpl

emen

tatio

ns a

lso

requ

ire a

vel

ocity

so

lutio

n, u

sual

ly fr

om a

n IN

S or

oth

er d

ead-

reck

onin

g se

nsor

. Fea

ture

mat

chin

g is

thus

not

an

inde

pend

ent n

avig

atio

n so

lutio

n or

tech

niqu

e; it

is in

deed

one

of

the

inte

grat

ed n

avig

atio

n sy

stem

s. M

oreo

ver,

all f

eatu

re m

atch

ing

tech

niqu

es a

re li

able

to o

ccas

iona

l err

oneo

us fi

x, d

ue e

ither

to th

e ag

e of

the

data

base

or,

whe

re th

ere

are

mul

tiple

mat

ches

, sel

ectin

g th

e w

rong

mat

ch. T

he in

here

nt in

tegr

ated

nat

ure

of fe

atur

e m

atch

ing

does

hel

p in

such

diff

icul

t sce

nario

s. 3

New

dev

elop

men

ts in

indo

or lo

catio

n te

chni

ques

bas

ed o

n te

rres

trial

radi

o si

gnal

s hav

e re

lativ

ely

rece

ntly

em

erge

d. S

yste

ms a

vaila

ble

on th

e m

arke

t use

si

gnal

s suc

h as

infra

red,

ultr

ason

ic a

nd ra

dio.

Mos

t of t

hese

syst

ems,

how

ever

, req

uire

exp

ensi

ve in

stal

latio

ns o

f a la

rge

num

ber o

f rec

eive

rs o

r tra

nsm

itter

s in

the

indo

or e

nviro

nmen

t. To

redu

ce in

stal

latio

n co

sts,

an a

ppro

ach

may

be

chos

en w

hich

mak

es u

se o

f alre

ady

avai

labl

e in

fras

truct

ure,

i.e.

, the

use

of W

irele

ss

LAN

(WLA

N o

r WiF

i).

4 M

obile

tele

phon

y m

etho

ds a

re d

ivid

ed in

to tw

o m

ain

subc

ateg

orie

s: te

rmin

al-b

ased

and

net

wor

k-ba

sed.

With

in th

ese

subc

ateg

orie

s are

AG

PS, S

IM-to

olki

t, ce

ll-ID

, OTD

A (o

bser

ved

time

diff

eren

ce o

f arr

ival

), U

L-TD

A (u

plin

k tim

e di

ffere

nce

of a

rriv

al),

E-O

TDA

(enh

ance

d O

TDA

), A

OA

(ang

le o

f arr

ival

), C

GI+

TA (c

ell g

loba

l ide

ntity

tim

ing

adva

nce)

, E-C

GI+

TA (e

nhan

ced

CG

I+TA

), m

atrix

, etc

. 5

Shor

t-ran

ge w

irele

ss n

etw

ork

tech

niqu

es in

clud

e th

e us

e of

WLA

N (I

EEE8

02.1

1), R

FID

, Zig

Bee

(IEE

E802

.15.

4), B

luet

ooth

, ad

hoc

netw

orks

, UW

B

(IEE

E802

.15.

3), u

ltras

ound

, GN

SS re

peat

ers (

Esm

ond

et a

l., 2

007;

Ben

sky,

200

8).

6 TV

, AM

and

FM

sign

als a

re c

alle

d ‘s

igna

ls o

f opp

ortu

nity

’ bec

ause

they

nor

mal

ly e

xist

for p

urpo

ses o

ther

than

loca

tion

dete

rmin

atio

n.

7 C

oope

rativ

e po

sitio

ning

met

hods

are

man

y, d

epen

ding

mos

tly o

n th

e op

erat

ing

envi

ronm

ent.

One

typi

cal e

xam

ple

is a

gro

up o

f firs

t-res

pond

ers o

n th

e pe

riphe

ry o

f an

inci

denc

e zo

ne (e

.g.,

a bu

rnin

g bu

ildin

g) p

rovi

ding

loca

tion

refe

renc

e da

ta (t

hrou

gh w

eara

ble

pseu

dolit

es o

r ad

hoc

netw

ork

sign

al so

urce

s)

to th

eir c

olle

ague

s ins

ide

the

dang

er z

one.

Firs

t-res

pond

ers i

nsid

e th

e da

nger

zon

e m

ay a

lso

exch

ange

loca

tion

refe

renc

e da

ta if

som

e of

them

hav

e ac

cess

to

unco

mpr

omis

ed p

rein

stal

led

asse

ts fo

r loc

atio

n de

term

inat

ion.


Loran too has been omitted from the table. As mentioned in Section 3.3, Loran is an internationally standardised positioning, navigation, and timing (PNT) service for use by many modes of transport and other applications. eLoran has been proved to have the capacity to provide the performance in accuracy, availability, integrity, and continuity needed for applications like aviation non-precision instrument approaches, maritime harbour entrance and approach, land-mobile vehicle navigation, and location-based services. It may also be deployed as a source of precise time and frequency for services like telecommunications. It is an independent and dissimilar complement to GNSS and allows GNSS users to maintain the safety, security, and economic benefits of GNSS even when their satellite services are disrupted by, e.g., deliberate signal jamming. Despite all these advantages of Loran, however, it has been phased out by the US Coast Guard and its global future outlook is arguably uncertain.

Figure 4 Assisted-GPS system architecture

Location server

Referencestations

Cellular network

GNSS satellites

A-GPS receiver

Technologies such as automatic identification systems (AIS) and long range identification and tracking system (LRIT) are still in currency but they have been omitted from Table 8 so as to keep the size of the table to proportion. These are used only in the maritime industry. Also omitted from Table 8 are point-based navigation systems, which provide horizontal positions using measurements from only one station, although multiple stations are applicable. These methods include non-directional beacon broadcasts (NDBs), VOR (VHF omnidirectional radio-range), and DME (distance measurement equipment). Details of these methods can be found in, e.g., Enge et al. (1995), and Uttam et al. (1997). Also left out of Table 8 is the use of sonar for underwater location. Radio navigation signals do not propagate underwater. Instead, submarines, remotely operated vehicles (ROVs), and autonomous underwater vehicles (AUVs) rely on sonar for underwater location (Butler and Verrall, 2001).

202 A. Musa et al.

A key to the success of logistics application of location is accurate georeferencing of the location obtained from a navigation system. Georeferencing involves relating the location or position to a map database, e.g., to identify the road on which a vehicle is travelling or a delivery van or a salesman is located. Systems that combine navigation and map database would be effective only if the following factors are fulfilled: affordability to the user; accuracy of approximately 20 m outdoors at 95% confidence level; accuracy of about 10 cm indoors at 95% confidence level; automatic initialisation without user assistance; effective display of location or position and location-based application; and a reliable map database.

5 Conclusions and future research

Location, navigation and precise timing have gradually become commodities, not just for logistics applications but for several other purposes. Location information, especially as derived from GPS, is now at the heart of most transportation capabilities, logistics and distribution industries, just-in-time manufacturing, emergency service operations, extractive industries, road construction, agriculture, etc. Even more notable is the fact that GPS, a system conceived and implemented entirely for positioning, provides the high-precision timing that forms the system backbone of many telephone networks, power grids, the internet, high-speed share trading, banking transactions, and many other key sectors of the economy and social infrastructure. Location information could be used, for instance, to support companies operating toll roads to collect fees without drivers having to stop, and charging them only for the exact distance they travelled. Other logistics and engineering projects that require a high-level of accuracy could also achieve centimetre-level measuring accuracy. Supplemental information could also be disseminated through new communication channels, in addition to the satellite broadcasts, such as via radio, SMS, GPRS, EDGE, WIDI, WiMAX and other emerging standards (Andrews et al., 2007).

This paper has presented requirements for location information for several logistics applications across industries. The information provided herein is handy and fulfils a need of the logistics industry and allied sectors, including the semiconductor industry. For specific projects and applications, however, it would be necessary to conduct detailed preliminary studies and assessments to determine the exact needs as well as technology and operational limitations. Table 8 provides a classification of the plethora of location technologies together with their capabilities as well as their relative advantages and disadvantages.

The special Delphi method introduced and operationalised by this paper is more laborious than the conventional Delphi approach but, since it uses a larger panel than the traditional method, its results are more robust by being more representative of reality. It may be used in other empirical investigations that rely on the Delphi method and where a larger panel or robustness of the results is desired or necessary.

5.1 Future research

It is recommended that the empirical methodology adopted in this paper be complemented with simulation studies, the complexities introduced by the myriad of application scenarios and available location technologies notwithstanding.


Experimentation with ‘probe missions’ is also needed to buttress and confirm the validity and utility of the estimated requirements.

There are several challenges that remain to be addressed in respect of location technologies for indoor and outdoor logistics, all of which offer avenues for further research. They include: signal multipathing and attenuation effects especially indoors; signal interference, particularly regarding the shared frequencies between GPS, pseudolites and IMES; height estimation, especially in indoor environments; estimating the heading when using MEMS-based sensors; the development of advanced, reliable and efficient signal processing and sensor fusion algorithms; empowering location and navigation devices to use contexts and learn and estimate places (and correctly suggesting place names), in addition to geo-coordinates, in order to speed up positioning even in signal-challenged environments and also to reduce power consumption; and generating so-called ‘2.5-dimensions’, in which altitude is represented with a symbolic name such as ‘parking level A’ or ‘3rd floor’. Height representation by 2.5-dimensions are more meaningful to the user than coordinate-based altitude like ‘3.6 metres above vertical reference’. Also, some of the challenges associated with specific positioning technologies, as highlighted in Table 8 against each method or technology, provide opportunities and challenges for further research.

The integration of multiple location sensors and systems often leads to non-linear and non-Gaussian estimation problems. For such problems the conventional extended Kalman filter may be inadequate and other filter types, such as unscented Kalman filter and/or the particle filter, may be more suitable. Unfortunately, these advanced filters generally have higher computational overheads, which in turn imply higher onboard power budgets and superior grade processors. Sensor fusion can be implemented as a centralised or decentralised filter, the major trade-off between them being optimum performance versus computational complexity.

References Abdel-Hamid, W., Abdelazim, T., El-Sheimy, N. and Lachapelle, G. (2006) ‘Improvement of

MEMS-IMU and GPS performance using fuzzy modelling’, GPS Solutions, Vol. 10, No. 1, pp.1–11.

Ahson, S.A. and Ilyas, M. (Eds.) (2011) Location-Based Services Handbook: Applications, Technologies and Security, Taylor and Francis, Boca Raton.

Air Services Australia (2012) Automatic Dependent Surveillance Broadcast (ADS-B): Frequently Asked Questions [online] http://www.airservicesaustralia.com/wpcontentuploads/ FAQ-ADS-B-Final-1-0-01NOV12_AIRSERVICES.pdf (accessed 20 August 2013).

Andrews, J.G., Ghosh, A. and Muhamed, R. (2007) Fundamentals of WiMAX: Understanding Broadband Wireless Networking, Prentice-Hall, New Jersey.

Azvine, B., Cui, Z. and Nauck, D. (2005) ‘Towards real-time business intelligence’, BT Technology Journal, Vol. 23, No. 3, pp.214–225.

Baker, A. (1998) ‘A survey of factory control algorithms that can be implemented in a multiagent hierarchy: dispatching, scheduling, and pull’, Journal of Manufacturing Systems, Vol. 17, No. 4, pp.297–320.

Barnes, J., Rizos, C., Wang, J., Small, D., Voigt, G. and Gambale, N. (2003) ‘High precision indoor and outdoor positioning using locatanet’, Journal of Global Positioning Systems, Vol. 2, No. 2, pp.73–82.

204 A. Musa et al.

Bartone, C.G. (2008) ‘Loran and research efforts at Ohio University’, ION Southern California Section Meeting, Torrance, CA, 16 December [online] http://socal.ion.org/wp-content/ uploads/2013/06/eLoran.pdf (accessed 09 September 2013).

Basker, S., Shaw, G., Williams, P. and Last, D. (2010) ‘Evolution from Loran-C to eLoran’, Prepared for the European eLoran Forum 2010 [online] http://www.glarrnav.org/pdfs/ evolution_from_loran_c_to_eloran_v11.pdf (accessed 09 September 2013).

Basnayake, C. (2009) ‘Positioning for driver assistance: communication on the road’, GPS World, Vol. 20, No. 4, pp.28–36.

Bensky, A. (2008) Wireless Positioning Technologies and Applications, Artech House, Boston, London.

Bestmann, U., Hecker, P., Kneissl, F. and Kropp, V. (2010) ‘Aviation applications: hybrid navigation techniques and safety-of-life requirements (part 2)’, Inside GNSS, Vol. 5, No. 5, pp.62–68.

Bestmann, U., Steen, M., Hecker, P., Konovaltsev, A., Heckler, M.V.T. and Kneissl, F. (2010) ‘Aviation applications: hybrid navigation techniques and safety-of-life requirements (part 1)’, Inside GNSS, Vol. 5, No. 4, pp.64-71.

Bilchev, G., Marston, D., Hristov, N., Peytchev, E. and Wall, N. (2004) ‘Traffimatics: intelligent cooperative vehicle highway systems’, BT Technology Journal, Vol. 22, No. 3, pp.73–83.

Butler, B. and Verrall, R. (2001) ‘Precision hybrid inertial/acoustic navigation system for a long-range autonomous underwater vehicle’, Navigation, Vol. 48, No. 1, pp.1–12.

Čapkun, S. and Hubaux, J.P. (2006) ‘Secure positioning in wireless networks’, IEEE Journal of Selected Areas in Communication, Vol. 24, No. 2, pp.221–232.

CSMG (2009) The Impact of Remote Asset Management Technologies on the Goods Transportation Industry, Report by CSMG, the Strategy Division of TMNG, Sponsored by SkyBitz [online] http://www.tmng.com/knowledge-center/research-reports/remote-assetmanagement-technology-goods-transportation-industry%20%20 (accessed 10 September 2013).

Dabbas, R.M. and Fowler, J.W. (2003) ‘A new scheduling approach using combined dispatching criteria in wafer FABS’, IEEE Transactions on Semiconductor Manufacturing, Vol. 16, No. 3, pp.501–510.

Enge, P.K., Swanson, E., Mullin, R., Ganther, K., Bommarito, A. and Kelly, R. (1995) ‘Terrestrial radio navigation systems’, Navigation (Journal of the Institute of Navigation), Vol. 42, No. 1, pp.61–108.

Esmond, E., Retscher, G. and Xia, L. (2007) ‘Minimum range error algorithm: RFID-GNSS integration for vehicle navigation in urban canyons’, Proceedings of 5th Symposium on Mobile Mapping Technology, Padova, Italy, 29–31 May.

FAA (2010) Airworthiness Approval of Automatic Dependent Surveillance Broadcast Out Systems, Advisory Circular AC No. 20-165, US Department of Transportation, Federal Aviation Administration [online] http://www.faa.gov/documentLibrary/media/Advisory_Circular/ AC%2020-165A.pdf (accessed 23 September 2013).

FAA (2011) Concept of Operations for the Next Generation Air Transportation System, Version 3.2, Joint Planning and Development Office (JPDO), FAA [online] http://www.dtic.mil/ cgibin/GetTRDoc?AD=ADA535795 (accessed 24 September 2013).

Finkelstein, R. (2009) EATR: Energetically Autonomous Tactical Robot: Project Overview, Robotic Technology Inc. [online] http://www.robotictechnologyinc.com/images/upload/file/ Presentation%20EATR%20Brief%20Overview%206%20April%2009.pdf (accessed 7 September 2013).

Friesz, T.L. (2007) Dynamic Optimization and Differential Games, Springer, New York. Goel, A. (2008) Fleet Telematics: Real-time Management and Planning of Commercial Vehicle

Operations, Springer, New York.


Grasman, S.E. (2006) ‘Dynamic approach to strategic and operational multimodal routing decisions’, International Journal of Logistics Systems and Management, Vol. 2, No. 1, pp.96–106.

Grejner-Brzezinska, D., Toth, C. and Moafipoor, S. (2007) ‘Pedestrian tracking and navigation using an adaptive knowledge system based on neural networks’, Journal of Applied Geodesy, Vol. 1, No. 3, pp.111–123.

Grubbs, F.E. (1969) ‘Procedures for detecting outlying observation in samples’, Technometrics, Vol. 11, No. 1, pp.1–21.

Harris, M. and Murphy, T. (2008) ‘Awareness in the air: rapid position updates for controllers and pilots’, GPS World, Vol. 19, No. 12, pp.40–46.

Hewitson, S. and Wang, J. (2010) ‘Extended receiver autonomous integrity monitoring (eRAIM) for GNSS/INS integration’, Journal of Surveying Engineering, Vol. 136, No. 1, pp.13–22.

Hodge, V.J. and Austin, J. (2004) ‘A survey of outlier detection methodologies’, Artificial Intelligence Review, Vol. 22, No. 2, pp.85–126.

Hsu, C., Levermore, D.M., Carothers, C. and Babin, G. (2007) ‘Enterprise collaboration: on demand information exchange using enterprise databases, wireless sensor networks, and RFID systems’, IEEE Transactions on Systems, Man and Cybernetics, Vol. A37, No. 4, pp.519–532.

ICAO (2012) Circular 326 – Assessment of ADS-B and Multilateration Surveillance to Support Air Traffic Services and Guidelines for Implementation (Cir 326 AN/188), Published by International Civil Aviation Organization.

ICAO (2013) ADS-B Implementation and Operations Guidance Document, Edition 6.0 [online] http://www.icao.int/APAC/Documents/edocs/cns/ADSB_AIGD6.pdf (accessed 24 September 2013).

ISO/IEC (2008) ISO/IEC 19762-5:2008, Information Technology, Automatic Identification and Data Capture (AIDC) Techniques, Harmonized Vocabulary, Part 5: Locating Systems [online] http://www.iso.org/iso/catalogue_detail.htm?csnumber=50718 (accessed 7 September 2013).

Jones, K.L. (2006) ‘Indoor positioning technologies for emergency response: overview of emerging and COTS solutions’, The Aerospace Corporation [online] http://www.wpi.edu/Images/CMS/ PPL/Aerospace.pdf (accessed 7 September 2013).

Kim, D., Langley, R.B., Kim, J.H. and Kim, S.N. (2003) ‘A gantry crane auto-steering system based on GPS RTK technology’, Proceedings of GNSS 2003, European Navigation Conference, Graz, 22–25 April.

Kitching, J., Knappe, S., Liew, L., Moreland, J., Schwindt, P.D.D., Shah, V., Gerginov, V. and Hollberg, L. (2005) ‘Microfabricated atomic frequency references’, Metrologia, Vol. 42, No. 3, pp.S100–S104.

Knappe, S., Gerginov, V., Schwindt, P.D.D., Shah, V., Robinson, H.G., Hollberg, L. and Kitching, J. (2005) ‘Atomic vapor cells for chip-scale atomic clocks with improved longterm frequency stability’, Optics Letters, Vol. 30, No. 18, pp.2351–2353.

Knappe, S., Liew, L., Shah, V., Schwindt, P., Moreland, J., Hollberg, L. and Kitching, J. (2004) ‘A micromachined atomic clock’, Applied Physics Letters, Vol. 85, No. 9, pp.1460–1462.

Kuo, C. and Huang, C. (2006) ‘Dispatching of overhead hoist vehicles in a FAB intrabay using a multimission-oriented controller’, International Journal of Advanced Manufacturing Technology, Vol. 27, Nos. 7/8, pp.824–832.

Manandhar, D., Okano, K., Ishii, M. and Torimoto, H. (2008) ‘Development of ultimate seamless positioning system based on QZSS IMES’, Proceedings of the 21st International Technical Meeting of the Satellite Division of the Institute of Navigation, Savannah, GA, 16–19 September.

Martin, S., Kuhlen, H. and Abt, Y.T. (2007) ‘Interference and regulatory aspects of GNSS pseudolites’, Journal of Global Positioning Systems, Vol. 6, No. 2, pp.98–107.

Mattos, P.G. (2008) ‘Self-assisted GPS: no server and no connection requirement’, GPS World, Vol. 19, No. 9, pp.50–56.

206 A. Musa et al.

Milde, M. (2008) International Air Law and ICAO, Eleven International Publishing, Utrecht, The Netherlands.

Mohleji, S.C. and Wang, G. (2010) Modeling ADS-B Position and Velocity Errors for Airborne Merging and Spacing in Interval Management Application, Center for Advanced Aviation System Development (CAASD), The MITRE Corporation [online] http://www.mitre.org/ work/tech_papers/2010/10_3026/10_3026.pdf (accessed 29 August 2013).

Moon, P. and Spencer, D.E. (1988) Field Theory Handbook, Including Coordinate Systems, Differential Equations, and Their Solutions, Springer-Verlag, New York.

Muckstadt, J.A. and Roundy, R.O. (1993) ‘Logistics of production and inventory’, Handbooks in Operations Research and Management, Vol. 4, North-Holland, Amsterdam.

Nagy, G. and Salhi, S. (2007) ‘Location and routing: issues, models and methods’, European Journal of Operational Research, Vol. 177, No. 2, pp.649–672.

Nguyen, C.T.C. (2007) ‘MEMS technology for timing and frequency control’, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol. 54, No. 2, pp.251–270.

Petrovski, I., Hojo, H. and Tsujii, T. (2008) ‘First AGPS, now BGPS: instantaneous precise positioning’, GPS World, Vol. 19, No. 11, pp.42–48.

Petrovski, I.G. (2003) ‘QZSS: Japan’s new integrated communication and positioning service for mobile users’, GPS World, Vol. 14, No. 6, pp.24–29.

Prasad, R. and Ruggieri, M. (2005) Applied Satellite Navigation Using GPS, Galileo and Augmentation Systems, Artech House, Boston.

Quddus, M.A. (2006) High Integrity Map-Matching Algorithms for Advanced Transport Telematics Applications, PhD thesis, Centre for Transport Studies, Imperial College London.

Quddus, M.A., Ochieng, W.Y. and Noland, R.B. (2006) ‘Current map-matching algorithms for transport applications: State of the art and future research directions’, Transportation Research (Part C), Vol. 15, No. 5, pp.312–328.

Quddus, M.A., Ochieng, W.Y. and Noland, R.B. (2006) ‘Integrity of map-matching algorithms’, Transportation Research (Part C), Vol. 14, No. 4, pp.283–302.

Retscher, G. (2006) ‘An intelligent multi-sensor system for pedestrian navigation’, Journal of Global Positioning Systems, Vol. 5, No. 1, pp.110–118.

Retscher, G. (2007) ‘Test and integration of location sensors for a multi-sensor personal navigator’, Journal of Navigation, Vol. 60, No. 1, pp.107–117.

Retscher, G., Moser, E., Vredeveld, D., Heberling, D. and Pamp, J. (2007) ‘Performance and accuracy test of a WiFi indoor positioning system’, Journal of Applied Geodesy, Vol. 1, No. 2, pp.103–110.

RFID Journal (2005) ‘UK’s Royal mail to improve with £2m RFID spend’ [online] http://www.rfidjournal.com/articles/view?6164 (accessed 7 September 2013).

Ristic, B., Arulampalam, S. and Gordon, N. (2004) Beyond the Kalman Filter: Particle Filters for Tracking Applications, Artech House, Boston.

Rollo, R. (2007) ‘Navigation in a nugget: SPAWAR leverages new chip-scale atomic clock’, GPS World, Vol. 18, No. 9, pp.56–58.

RTCA (2002) Minimum Aviation System Performance Standards for Automatic Dependent Surveillance Broadcast (ADS-B), DO-242A, RTCA, Inc. [online] http://adsb.tc.faa.gov/ WG6_Meetings/Meeting%2016/WG6-WP16-04- Working%20Draft_242B_Body_V1.pdf (accessed 24 September 2013).

RTCA (2006) Minimum Operational Performance Standards for 1090 MHz Extended Squitter Automatic Dependent Surveillance Broadcast (ADS-B) and Traffic Information Services Broadcast (TIS-B), DO-260A. RTCA, Inc. [online] http://adsb.tc.faa.gov/WG3_Meetings/ Meeting21/DO-260-Change-1.pdf (accessed 24 September 2013).

Sarma, A.D., Sultana, Q. and Srinivas, V.S. (2010) ‘Augmentation of Indian regional navigation satellite system to improve dilution of precision’, Journal of Navigation, Vol. 63, No. 2, pp.313–321.


Shim, J.P., Warkentin, M., Courtney, J.F., Power, D.J., Sharda, R. and Carlsson, C. (2002) ‘Past, present, and future of decision support technology’, Decision Support Systems, Vol. 33, No. 2, pp.111–126.

Simsky, A., Wilms, F. and Franckart, J.P. (2004) ‘GNSS-based failsafe train positioning system for low-density traffic lines based on one-dimensional positioning algorithm’, Second ESA Workshop on Satellite Navigation User Equipment Technologies, ESA/ESTEC, Noordwijk, The Netherlands, 8–10 December.

Singh, N. (2003) ‘Emerging technologies to support smart organization management’, Communications of the Association of Computing Machinery, Vol. 46, No. 9, pp.243–247.

Thienelt, M., Eichhorn, A. and Reiterer, A. (2007) ‘WiKaF: a knowledge-based Kalman-filter for pedestrian positioning, location based services and telecartography’, Lecture Notes in Geoinformation and Cartography, pp.143–152, Springer, Berlin.

Thiesse, F. and Fleisch, E. (2008) ‘On the value of location information to lot scheduling in complex manufacturing processes’, International Journal of Production Economics, Vol. 112, No. 2, pp.532–547.

Uttam, B.J., Amos, D.H., Covino, J.M. and Morris, P. (1997) ‘Terrestrial radio navigation systems’, in Kayton, M. and Fried, W.R. (Eds.): Avionics Navigation Systems, pp.99–177, Wiley.

van Diggelen, F. (2009) A-GPS: Assisted GPS, GNSS, and SBAS, Artech House, Boston, London. van Eijs, M.J.G. (1994) ‘Multi-echelon inventory systems with joint ordering and transportation

decisions’, International Journal of Production Economics, Vol. 35, Nos. 1/2/3, pp.285–292. van Hees, J. (2007) ‘GPS-GNSS technology for container yard operations’, Septentrio Satellite

Navigation, Leuven, Belgium. Warren, P.W. (2004) ‘From ubiquitous computing to ubiquitous intelligence’, BT Technology

Journal, Vol. 22, No. 2, pp.28–38. Waters, D. (2003) Global Logistics and Distribution Planning, Kogan Page, London. Williamson, O.E. (2008) ‘Outsourcing: transaction cost economics and supply chain management’,

Journal of Supply Chain Management, Vol. 44, Nol. 2, pp.5–16. Win, M. and Scholtz, R. (1998) ‘On the performance of ultrawide bandwith signals in dense

multipath environment’, IEEE Communication Letters, Vol. 2, No. 2, pp.51–53. Xi, L., Jun, Z., Yanbo, Z. and Wei, L. (2009) ‘Surveillance accuracy analysis of ADS-B supporting

the separation service in Western China’, Proceedings of Integrated Communications, Navigation and Surveillance Conference (ICNS ‘09), 13–15 May, pp.1–6.

Yang, G.K. (2007) ‘Note on sensitivity analysis of inventory model with partial backorders’, European Journal of Operational Research, Vol. 177, No. 2, pp.865–871.

Zeimpekis, V., Tarantilis, C.D., Giaglis, G.M. and Minis, I. (2007) Dynamic Fleet Management: Concepts, Systems, Algorithms and Case Studies, Springer, New York.

Ziedan, N.I. (2006) GNSS Receivers for Weak Signals, Artech House, Boston. Zographos, K. (2003) Implications, Future Developments, Needs and Roadmap for Implementation

of Emerging Supply Chain Management and Logistics Concepts, Final Report of Business, Policy and Research Implications of Logistics in the e-Economy Environment Project, Contract No IST-2001-38477, European Commission.

208 A. Musa et al.

Appendix

ADAS Advanced driver assistance system. ADS-B Automatic dependent surveillance broadcast. AGPS Assisted GPS. A cold start for a GPS receiver typically takes between 60 seconds

to 12 minutes. A warm start takes about 30 seconds in ideal conditions, and a hot start takes 6 seconds or more. AGPS can reduce the TTFF (time to first fix of position) by supplying current ephemeris and accurate time over a communications connection. In some situations, TTFF can be reduced to just one or two seconds, the time needed to acquire only one subframe of navigation data, to retrieve the time mark. However, the receiver does need a network connection to the source of the assistance data, or direct USB access to a PC. The receiver thus cannot operate autonomously. Moreover, it is often impossible to access time information through a communications network accurate enough to obviate reading at least one subframe of the navigation message. Then there is the issue of privacy: users may just want to navigate without identifying themselves and revealing their location to the network assistance provider. There is also the issue of interference between voice calls and GPS functions on mobile phones, requiring the user to wait until all the data from the navigation message is acquired before placing calls. Assisted GPS protocols include those using GSM, GPRS, or CDMA networks. In GSM the assistance data is specified in the Radio Resource Location Services Protocol (RRLP), and in UMTS it is given in Radio Resource Control (RRC). There are also user-plane solutions, e.g., Open Mobile Alliance’s Secure User Plane Location (SUPL), which effectively transmits the same information over packet-switched networks that are specified for circuit-switched networks in RRLP and RRC.

AGV Automated guided vehicle. AIS Automatic identification systems. ALV Automated lift vehicle. APV Approach procedures with vertical guidance (with APV-I and APV-II. See

Section 3.2). ASSA Airport surface situational awareness. AUV Autonomous underwater vehicles. BGPS The ‘B’ in the acronym ‘BGPS’ simply means ‘this comes after A’. BGPS

positively answers the question of whether it is possible to realise AGPS without requiring a network and without reading a navigation message from a satellite signal (Petrovski et al., 2008).

CAPS Chinese area positioning system. Less well known than Beidou and Compass, even in the navigation community, is China’s other regional satellite navigation system called CAPS. This operates on C-band frequencies, instead of the L band in which most GNS systems operate. CAPS also differs from all other GNS systems in the sense that the navigation messages are generated on the ground and uploaded to the communications satellites, with the satellites serving only as transponders.

CAT Category (with CAT-I, CAT-II, etc. See Section 3.2). CR Containment radius of position fix.


CSAC Chip-scale atomic clocks. This an emerging technology that is still in its infancy (Kitching et al., 2005; Knappe et al., 2004, 2005). Applications have so far been limited to the military. Of the most significant sources of errors and computational overheads in positioning with GNSS is the fact that the receiver clocks are relatively cheap but imprecise. CSAC technology hopes to make affordable atomic clocks of chip size, for incorporation in high-end GNSS receivers. The ‘positioning nugget’ technology represents the convergence of a CSAC with a deeply integrated MEMS inertial measurement unit, a GPS M-code software-defined receiver (SDR), and particle-filtering accelerator (Ristic et al., 2004; Rollo, 2007). If a GNSS receiver has a tiny atomic clock that is synchronised with the atomic clocks of the GNS system, then one of the major equations the receiver CPU has to solve disappears and the following become realisable: significantly reduced TTFF; reduced position error for time and altitude with fewer satellites in view; increased anti-jamming and anti-spoofing capability; decreased GNSS reacquisition time when the signal is temporarily lost; the GNSS transceiver can become a master member of a cooperative positioning network, i.e., it can broadcast its location corrections and precise time to other receivers in the network.

DARPA Defence Advanced Research Projects Agency of the USA. DASH7 Developers’ Alliance for Standards Harmonization of ISO 18000-7. Unlike most

active RFID technologies, DASH7 supports tag-to-tag communication. dB Decibel. DGPS Differential GPS. DME Distance measurement equipment. DSRC Dedicated short-range communication. DSS Digital signal standard. EDGE Enhanced data rates for GSM evolution. EEBL Emergency electronic brake light. EGNOS European geostationary navigation overlay service (see SBAS). EPU Estimated position uncertainty. Exif Exchangeable image file format (often incorrectly written as EXIF) is a standard

that specifies the formats for images, sound, and ancillary tags used by digital cameras (including smartphones), scanners and other systems handling image and sound files recorded by digital cameras.

FAA US Federal Aviation Authority. FARO Final approach and runway occupancy awareness. FCC US Federal Communications Commission. FCW Forward collision warning. GAGAN India’s GNSS-aided geosynchronous augmented navigation system (see SBAS). GAST-D GBAS Approach Service Type D. GBAS Ground-based augmentation systems. GDP Gross domestic product. GLONASS Russia’s global navigation satellite system. GNSS This is a generic term for global satellite navigation system. GPRS General packet radio service. HS-GPS High-sensitivity GNSS. ICAO International Civil Aviation Organization.

210 A. Musa et al.

IMES Japan’s indoor messaging service/system. This is composed of transmitters, GPS receivers with modified firmware embedded in mobile terminals and servers. It aims to provide seamless positioning everywhere indoors. The system has been developed by Japan’s Aerospace Exploration Agency (JAXA), GNSS Technologies, and Lighthouse Technology and Consulting. Hitachi Ltd is also working on a similar system. It relies on satellite signals outdoors but uses signals from IMES transmitters indoors. The IMES signal structure is similar to that of GPS, except for the content of the navigation message. Thus, the same receiver can be used for both GPS and IMES. An IMES transmitter sends an RF signal similar to that of GPS and QZSS, suggesting its 3D location, the position of the center of its cell coverage area, or linking the receiver to a database that provides the location and other characteristics of the transmitter. Instead of the ephemeris data, clock corrections, ionospheric parameters, etc., contained in the GPS navigation message, the IMES message periodically broadcasts position and additional information in a similar format. IMES uses the same L1 centre frequency as GPS and QZSS, and the same BPSK modulation. IMES’s dedicated spread spectrum codes are from the same family of Gold Codes as GPS and QZSS (numbers 173 to 182 from the C/A code assignment table). The power of each IMES transmitter is low (0.1 to 0.4 nanowatts) that it can only be acquired within about 10 m of the transmitter. Any GPS receiver that can decode PRNs 173 through 182 can receive and decode IMES signals.

IMU Inertial measuring unit. The sensor unit containing inertial sensors (accelerometers and gyros).

INS Inertial navigation system. IP Internet Protocol. IP address location data can include information such as

country, region, city, postal/zip code, latitude, longitude and time zone. Deeper data sets can determine other parameters such as domain name, connection speed, ISP, language, proxies, company name, US DMA/MSA, NAICS codes, and home/business.

IPTC The International Press Telecommunications Council, based in London, UK, is a consortium of the world’s major news agencies and news industry vendors. It develops and maintains technical standards for improved news exchange that are used by virtually every major news organisation in the world.

IRNSS Indian regional navigation satellite system (see SBAS). IVS In-vehicle signing. LAAS GPS local area augmentation system. LBS Location-based services. LCA Lane change advisor. LiDAR Light detection and ranging. LNAV Lateral navigation. LPV Localizer performance with vertical guidance. LRIT Long range identification and tracking system. MASPS Minimum aviation system performance standards. MEMS Micro-electro-mechanical system. A manufacturing process that, e.g., enables the

design and fabrication of miniaturised, lightweight, power efficient, and potentially inexpensive sensors, including accelerometers, gyros and magnetometers (Nguyen, 2007).


MS Mobile station. MSAS Japan’s MTSAT-satellite-based augmentation system (see SBAS). MTSAT Japan’s multifunction transport satellite. NAC-P Navigation accuracy category for position. NDB Non-directional beacon broadcast. NIC Navigation integrity category. NRA Non-radar airspace. NRTK Network real-time kinematic positioning. OEM Original equipment manufacturer. PNT Positioning, navigation, and timing. PPP Precise point positioning by GNSS signals. QZSS Japan’s quasi-zenith navigation satellite system (see SBAS). The inclined

geostationary orbits of the QZSS satellites have been designed so that there is always one satellite above 70-deg in Japan. This dramatically improves position determination in Japanese cities: the three satellites of the QZSS constellation provide much better high-elevation coverage over Japanese cities than the 30 GPS satellites combined (Petrovski, 2003).

RAD Radar airspace applications. RAIM GPS receiver autonomous integrity monitoring. RFID Radio frequency identification. RNAV Aerial navigation. ROV Remotely operated vehicle. RSA Rivest-Shamir-Adleman public-key algorithm. RTCA Radio Technical Commission for Aeronautics. SAGPS Self-Assisted GPS. Rather than access assistance data through a TCP/IP link to a

remote server, or by direct connection to a PC, this approach generates an extended ephemeris on the mobile device itself directly, requiring no access to the internet whatsoever (Mattos, 2008). As a reference, the method uses a recent, if expired, ephemeris for the satellites in view, and revises it by employing the known perturbing effects of the Sun, Moon, Earth’s oblateness, solar flux, etc. In clear skies with unobstructed satellites, there is a slight degradation of the accuracy of this method, as measurements are then good and satellites abundant, but ephemeris is degraded. The aim is to provide standalone ephemeris prediction for PNDs on start-up within 5 to 10 seconds after being switched off for up to 3 days, instead of the traditional 30 second warm-start, which can extend to minutes in urban canyons, or on highways with light poles. Because of the random walk of satellite clocks, this approach does not support predictions longer than 3 days without new ephemeris.

212 A. Musa et al.

SBAS Space-based augmentation systems. Augmentation systems with public stake and which use geostationary satellites include North America’s WAAS, Europe’s EGNOS, Japan’s QZSS, Japan’s MSAS, India’s GAGAN, and China’s Beidou-1. QZSS’s main application is to supplement GPS by increasing the number of satellites visible in urban areas and mountainous regions. It provides GPS differential corrections to higher resolutions than MSAS (ICAO, 2012). GAGAN differs from IRNSS, another of India’s regional satellite navigation system. IRNSS’s service area is from longitude 40-deg to 140-deg and the planned accuracy within India is about 20 m (1-sigma) horizontally and vertically. Three of the seven IRNSS satellites will be geostationary and shared with the GAGAN SBAS system. The other four satellites will be divided between two geostationary orbits, inclined at 29-deg and crossing the equator at 55-deg and 112-deg (Sarma et al., 2010). China’s regional Beidou-1 system is currently being upgraded to a full global constellation called Beidou-2 or Compass. It will have 5 geostationary (GEO) satellites, 4 middle earth orbit (MEO) satellites, and 5 inclined geosynchronous orbit (IGSO) spacecrafts. The full Beidou-2 (Compass) system is planned to be operational in 2020 and will have 5 GEOs, 3 IGSOs, and 27 MEOs. Commercial SBAS outfits include OmniStar and StarFire.

SDR Software-defined radio. SIL Surveillance integrity level. SMS Short message service. TTFF Time-to-first-fix in the use of GNSS for finding location. UUID Universally unique identifier. An identifier standard used in software

construction, standardised by the Open Software Foundation (OSF) as part of the Distributed Computing Environment (DCE).

UWB Ultrawide band. V2I Vehicle-to-infrastructure. V2V Vehicle-to-vehicle. V2X The group of common underlying system components of V2V and V2I

communication. VII Vehicle infrastructure integration. VNAV Vertical navigation. VOR Very high frequency (VHF) omnidirectional radio-range. WAAS North America’s wide area augmentation system (see SBAS). WHOIS A query and response protocol that is widely used for querying databases that

store the registered users or assignees of an internet resource, such as a domain name, an IP address block, or an autonomous system, but is also used for a wider range of other information. The protocol stores and delivers database content in a human-readable format.

WiDi Wireless display. WiMAX Worldwide interoperability for microwave access. The interoperable

implementations of the IEEE 802.16 family of wireless network standards ratified by the WiMAX Forum.

WLAN Wireless local area networks. XMP Extensible metadata platform. XMP is an ISO standard, originally created by

Adobe Systems Inc., for the creation, processing and interchange of standardised and custom metadata for all kinds of resources.

ZUPT Zero velocity update.

an assessment of location data requirements in logistics

Documents

operations management

logistics ahmed musa

uk email

university of newcastle

operations research

usa email

process management

ahmadu bello university