© 2001 mercury computer systems, inc. underwater tactical operations center (utoc) david a. toms...
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© 2001 Mercury Computer Systems, Inc.
Underwater Tactical Operations Center
(UTOC)
Underwater Tactical Operations Center
(UTOC)
David A. Toms
Mercury Computer Systems
2© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
OutlineOutline Trends in tactical C4ISR:
1991: TOCs can’t get enough intel support 2002: TOCs are inundated with intel products Targeting timelines are increasing! New tools are required to process the data
USAF/USA TOCs are migrating toward mobile, lightweight, open architectures
Technology demonstrations at Mercury Intelligent Bandwidth Data Compression Aided Target Recognition Multi-Hypothesis Target Tracking Geo-registration
Open Wings A new architecture for tactical op centers
3© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
High-Value Targets
Military ConvoysMassed Forces
Function of Underwater Tactical Operations Center Provide Surveillance Operator with Unified Tactical Picture via GIG Tools to Review Sensor Information, Provide Contextual Information Remove Sensor Clutter, Fuse Target Information
UTOCProcessing
ProcessingExploitation
(Sensor)Tasking
Dissemination
Processing
Processing
Collection Platforms
‘Common Operational Picture’
UTOC ISR SystemUTOC ISR System
4© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
UTOC ProcessingUTOC Processing
‘TPED Crisis’ Trained Image Analyst can
Process 10-30 Full-Scene 1Mega-pixel SAR Images/Hr (Global Hawk Will Generate ~6,000 Images/Hour)
Trained Surveillance Operator can Track 3-6 Targets (Joint STARS will Generate 10,000 Target Reports per second)
Trend Semi and Fully Automated
Tracking, Registration, ATR, Data Fusion
Semi-Automated Situation Assessment, Sensor Tasking TPED: Tasking, Processing, Exploitation, and Dissemination
PD: Probability of Detection, FAR: False Alarm Rate
Assisted Exploit.
ATR only
IA only
PD
FAR
How Well do IAs Classify Targets?
Dr. John M. Irvine, SAICPresentation at ATR Transition Conference, MIT Lincoln Lab, June 7, 2000
5© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Processing Algorithms Processing Algorithms
Tracking
ATR
Fusion
PatternAnalysis
Filtering
Detection
SituationAssessment
Algorithm
Phy
sics
Geo
met
ryS
tatis
tical
Rul
e-B
ased
Model
Information Processing
KnowledgeProcessing
Intelligence
Type
Signal Processing
Data Processing
Processing
10 - 100GFLOPS
100s of GFLOPS
Throughput
Amount of Sensor Data (100s of MB/s)
Dec
reas
ing
Am
ount
of
Dat
a
Incr
easi
ng D
esire
d In
form
atio
n
Impact
MercuryDomain
6© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Signal and Data Processing Architecture
Signal and Data Processing Architecture
MTI SignalProcessing (e.g., STAP)
SAR ImageFormation
SARRegistration
MTI TargetDetection
MTIRegistration
SAR TargetDetection
Video/IRRegistration
TargetDetection
SAR FeatureExtraction
FeatureExtraction
HRR FeatureExtraction
ATR
2D ATR
1D ATR
TrackingSensor
Tasking
Multi-Sensor/Multi-LookATR Fusion
Chip-Level ProcessingImage Processing
Report ProcessingSignal Processing
Video/IR Signal
RadarSignal
Sensor Mode/Look Region
Image-Level Processing
‘Data’ Processing
Image ChangeDetection
Fire ControlSystems
Signal Analysis Registration
ESM
7© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
UTOC Data FusionUTOC Data Fusion
Types of Sensor Data to be fused: Synthetic Aperture Radar imagery Ground Moving Target Indicator reports Electro-optic/Infrared imagery Hyperspectral imagery SIGINT/ELINT reports COMINT data BDA Chem/Bio/WMD reports Minefield delimitations Unattended sensors
8© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Stand-Alone DemonstrationsStand-Alone Demonstrations
Tools are required to analyze all the data
Completed demonstrations: Intelligent Bandwidth Compression (Sandia
Labs/Black River Systems/Mercury) Model-based ATR Algorithm (DARPA) Geo-Registration (DARPA)
Under Development Multiple Hypothesis Tracking (DARPA)
9© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Intelligent Bandwidth CompressionIntelligent Bandwidth Compression
Full-Scene Image Compressed After Target Chips Have Been Detected High Ratio for Background Low Ratio for Target Chips Overall Ratio ~128:1
10© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
GMTI Tracking FunctionGMTI Tracking Function
Generate Target Tracks Based on MTI Radar Reports
Tracker has to Account for Non-constant Target Velocities Measurement Errors Missed Detections False Reports
MTI REPORTS
TRACKS
11© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
GMTI Tracking ApproachGMTI Tracking Approach
PREDICTTRACKS
PREPROCESSREPORTS
GATE REPORTSWITH TRACKS
UPDATETRACKS
TRACKHYPOTHESIS
MANAGEMENT
MTIReports
DTEDData
RoadData
DTEDData
RoadData
TargetTracksConstrained
MTI Reports
Report/TrackPairs
Updated TrackHypotheses
Predicted TrackHypotheses
Retained TrackHypothesesTime
Multitarget Tracking Associate Reports for Tracks Filter out Measurement Noise by Averaging
Multiple Hypothesis Approach (MHT) Form Multiple Hypotheses for Report
Associations and Target Kinematics Select Most Likely Hypothesis After Processing
Multiple Frames of MTI Reports
CREATENEW TRACKS
SearchProblem
12© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Image Registration FunctionImage Registration Function Provides Spatial Correspondence Between Two Images Image Registration Prerequisite for Performing Change
Detection
Registration Results: Alan Chao, Alphatech
13© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Image Geo-Registration ApproachImage Geo-Registration Approach
Two-step Procedure
Image Geocoding (Image Ortho-rectification): Image Projected to a Common Reference Frame
Image Registration: Uses Image Data (Pixel Intensities or Image Feature) to Find Spatial Correspondence Between Images
ImageGeocoding
ImageRegistration
Images
SystemError Statistics
GeocodedImages
GeocodingError Statistics
RegisteredImages
RegistrationError Statistics
RelativeGeometry
SearchProblem
14© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Image Registration RequirementsImage Registration Requirements
Function of Feature or Pixel Intensity Approaches Features Used (e.g., Topological, Region, Object) Matching Algorithm (e.g., Hausdorff Distance,
Bayesian Metric) Desired Accuracy
Preliminary Estimates (Feature-Based Algorithm for SAR Image Registration) ~450x350 Pixel SAR Image 10 -100 Giga operations
Processing Requirements are Function of Input Rate, Data Characteristics, Desired Performance
15© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
ATR FunctionATR Function
Classify Target Based on Image Chip 2-D ATR: Uses High-Res SAR Image Data 1-D ATR: Uses High-Res Range Profile from
Radar MTI Data (Research Area)
T72Confidence:0.95
2-D ATR 1-D ATR
SCUD TELConfidence:0.7
Range-DopplerTarget Chip
SARTarget Chip
Range-Profile
16© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
2-D ATR Approach2-D ATR Approach
Traditional Approach: Template-Based Store Target SAR Templates for Various
Poses, Articulation Find Best Match and Declare Target Type
Model-Based Approach (Research) Store Wire-Frame Model for Various Target
Types Predict, Evaluate, Match, Search for Best
Match of Pose and Articulation
17© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
2-D ATR Requirements2-D ATR Requirements
Preliminary Estimates From Demo System Chip-Level Parallel Processing
Approx. 40 Mega operations per Chip
Ground Truth
System call & score, if correct
System call & score, if incorrect
T72 T72 BTR70 SA8 ZSU T72 BTR70ZSU SCUD T72
T72 BTR70
ZSU T72SCUD SA8ZSUBTR70 ZSUBTR70SA8ZSU
T72 T72 BTR70 SA8 ZSU T72 BTR70ZSU
T72 T72 T72BTR70 SA8 ZSU T72 BTR70 SCUD.95.90 .85 .80 .95 .95 .65 .80 .90
Click on image chip to inspect
ATR details
Click on image chip to inspect
ATR details
18© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Model-Based ATR AlgorithmModel-Based ATR Algorithm
Type (x,y) ScoreM2 35,87 10 0.91M548 38,88 14 0.83BMP2 32,89 192 0.05...
Focus ofAttention
Index
Search
Predict
Match
Extract
SAR Image
Detect
Scene Hypothesis
ROIs
ROI
PredictedFeatures
ExtractedFeatures
Evaluations
Scene Model
CoarseHypotheses
Cue
Explain
Verify
19© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Mercury Role in UTOCMercury Role in UTOC
Established Leader in Signal Processing Expertise in Sensor Algorithm Technology Middleware to Support Application Development Low space, weight and power requirements
Mercury HPC Architecture Well-Suited for Data Processing Can be Scaled to Support Improvements in Sensor
Resolution Supports Algorithms Requiring Tight Coupling
Between Signal & Data Processing Functions Testing underway at WPAFB Sensor laboratory
20© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Participation in Ground Station Activities: Openwings
Participation in Ground Station Activities: Openwings
OpenwingsArchitecture
HPCUTOC
Dom
ain
Exa
mpl
eProcessingRequirements
Container
Specifications
Openwings: Architecture for Plug-and-Play, Network Centric, Service Oriented System
Mobile Ground Stations is a Domain Example
Mercury is on Expert Team Analyzing Ground Station
Processing Requirements Developing HPC Container
Specifications• Life Cycle Support for an
Application• Clustering of Processors• Process Load Balancing www.openwings.org
21© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
Program OverviewProgram Overview
Openwings initiative established June ‘99 as a Joint IR&D effort between Motorola & Sun
Motorola and Sun Microsystems to lead a community in the development of a distributed, self-forming architecture
Mercury will provide High Performance Computing engines
Architecture development will be done using an open development approach
Initial framework is available to the Openwings community
22© 2001 Mercury Computer Systems, Inc. Ground Stations 1.5
SummarySummary
If submarines are to become full players in network centric warfare, then accessing and exploiting all available data sources will become essential
We are performing groundwork to show Mercury’s computers can meet these requirements Conducting data processing requirements analysis
and preparing demonstrations
These tools could be used for sonar data exploitation as well.