9 cosofret standoff explosives detection using airisenergetics.chm.uri.edu/?q=system/files/9...

Presentation Title October 18, 2009

Speaker Name 1

Physical Sciences Inc. 20 New England Business Center Andover, MA 01810

PhysicalSciences Inc.

B.R. Cosofret, T.E. Janov, M. Costolo, S. Chang, W.J. Marinelli, R. Moro, D.

Brown, and J. Oxley9 October 2009

Standoff detection of trace level explosive

residue using passive LWIR hyperspectral

imaging

Physical Sciences Inc.

Outline

• Program Overview• Strategic Framework• Technical Approach• Technology Overview• Summary of Test Results• Next Steps, Challenges


Speaker Name 2


Program Overview

• Ultimate goal: Develop sensor to attack terrorist networks– Covert & Passive standoff detection of explosive residues on surfaces

• Goal of S&T efforts: Assess and demonstrate the capability to detect trace level explosive residue on surfaces using passive LWIR hyperspectral imaging

• Technical Objectives:– Library signature development as a function of environmental conditions

– Demonstrate wide area detection from true standoff ranges (10 - 100m)

– Demonstrate detection and identification of explosives (RDX, TNT, PETN, TATP, UN, AN, C4, dynamite) present at low surface densities

– Conduct sensor performance evaluation as a function of contamination loading, range, environmental conditions, surface types, interferents, vehicle speed


Strategic Framework for Standoff Explosive Detection


Speaker Name 3


Strategic Framework:Program Plan to Build an IED

Concept Development

Identify targets

Device structure

Triggering mechanisms

Explosives

Device Packaging

Concealment

UXO

CONOPs

Concept Development

Identify targets

Device structure

Triggering mechanisms

Explosives

Device Packaging

Concealment

UXO

CONOPs

Acquisition

Recruit personnel

Identify sources

UXO or explosives

Triggers

Packaging

Concealment

Move parts to assembly bldg

Acquisition

Recruit personnel

Identify sources

UXO or explosives

Triggers

Packaging

Concealment

Move parts to assembly bldg

Weaponization

Modify UXO

Build new Device

Build trigger

Test trigger

Build packaging

Build concealment

Integrate System

Cache or deploy

Weaponization

Modify UXO

Build new Device

Build trigger

Test trigger

Build packaging

Build concealment

Integrate System

Cache or deploy

Deployment

Select target

Recon target area

Prep target site

Select CONOPs

Assault Force movement

Move and emplace IED

Rehearse Attack

PSYOPs movement

Initiate attack

Escape

PSYOP dissemination

Lessons learned

Deployment

Select target

Recon target area

Prep target site

Select CONOPs

Assault Force movement

Move and emplace IED

Rehearse Attack

PSYOPs movement

Initiate attack

Escape

PSYOP dissemination

Lessons learned

Command Authority

Finance PersonnelFacilities Equipment

Command Authority

Finance PersonnelFacilities Equipment


Targets and Detection Methodology

ResidueTransfer

FugitiveEmissions


Speaker Name 4


Strategic Framework:How Low (Sensitivity) Do You Need To Go?

• Fabricating an IED contaminates its maker, who spreads detectable residues – the trail to finding them

• High resolution imaging provides a richer target set– Spatial discrimination & awareness of residues

• Fluorescent dye studies indicate spot concentrations that are exploitable with a passive LWIR hyperspectral imager


Technology Overview


Speaker Name 5


Technical Approach - Explosive Identification

• Detection & Identification Basis– Molecular absorption spectroscopy

Detect changes in reflectance of IR radiation from surfaces due to presence of explosive residue

– Characteristic explosive spectral “finger prints” in LWIR region (7 – 12 µm)

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TATPAmmonium NitrateAmmonium PerchloratePotassium NitratePotassium PerchlorateNitromethane

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Wavelength (um)

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orpt

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ficie

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TetrylTNT

Exploitable Absorption Features of TypicalHomemade & Military Grade Explosives


Contamination Layer

Surface

Direct Thermal Emission from Contamination (Path 2)

Thermal Emission from Surface (Path 4)

Reflection of Background Radiance (Path 1)

Background Radiance

Simplified Surface Reflection Model

Reflected Thermal Emission from Contamination (Path 3)

• Contamination detected as differential change in reflectance due to reflection/absorbance of background thermal radiation

• Model sensor signal as linear combination of radiances from eachpath


Speaker Name 6


• Contaminant layer in thermodynamic equilibrium with surface (NS = NC)

Combined Path Radiances

)1)((2)1( SBSSBSSD NNNNN εαρεε −−+−+=

Surface Radiance

Background Radiance

Reflected from Surface

Background Radiance Modulated by Contaminant Layer and Reflected from

Surface

“Background” “Target Differential Radiance”

• Does not consider impact of atmospheric transmission

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Ext

inct

ion

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ffici

ent (

m2/

mg)

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ianc

e (W

/(cm

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))

Wavelength (um)

Surface Radiance (Ns) E = 1.0Signal without RDXSignal with RDXRDX Extinction

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Nor

mal

ized

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nsity

Wavelength (um)

RDX Reference Spectrum

Extracted RDX (Normalized)


• Leverages standoff system developed for chemical weapon agents and toxic industrial chemicals

– Fabry-Perot Interferometer provides rapid sequential sampling of pre-programmed discrete spectra

– FPGA-based real time processor provides spatial-spectral detection– Integrated advanced algorithms for “on the move” detection of chemical releases without a priori

knowledge of background

– Simultaneously detects up to 4 materials using 20 spectral bands in 200ms

– Larger explosive databases possible in 10 - 30 seconds

The SED SystemAdaptive Infrared Imaging Spectroradiometer (AIRIS)

Real-Time Wide Area Detection of CWAs, TICs, & Bio-

aerosols


Speaker Name 7


AIRIS-WAD Technology Overview

• 32o x 32o FOV direct imaging

• Detections overlaid on thermal infrared image of scene using a real-time processor

• Color coded target identification

• Data acquired and processed at 5 per second

• 10 meter spatial resolution at 5 km range for smaller release detection

• Archival data storage

• High speed tunable bandpass filter coupled to infrared focal plane array

• Detection of nerve and blister agents

• Intended deployment on vehicles, rotorcraft, and aircraft

• Built to be qualified to MIL-STD-810F for Shock, Vibration, Drop, and Temperature and MIL-STD-461/462 for EMI

Ground Airborne

Dugway Simulant ReleaseImaging

Lens Interferometer

Cold Shield

Cold Filter

Focal Plane Array

IR Camera


Summary of Experimental Program


Speaker Name 8


Thumb Smudge of Comp B

Detection on Non-Porous Real World Surfaces – Feasibility Assessment

• Detection on a variety of non-porous metal surfaces demonstrated

– Semi-quantitative approach

• Inability to detect on exterior glass surfaces not yet understood

– Could be related to IR coatings used on auto glass

SF-96

R134a

TNT

RDX

RDX

5 m

5 m


Detection Capability as a Function of Range

• Detection demonstrated to 20 meters using RDX

• Ranges to 100 meters possible depending on humidity and concentration levels

• Optics optimization required to align spatial resolution with CONOPS

• At 20 meters detected RDX spot is only 2x2 pixels

– ATR could flag operators– Zoom lens needed

15 m 20 m

5 m

SF-96

R134a

TNT

RDX

Automobile Trunk Lid

RDXRDX

RDXRDX


Speaker Name 9


Quantitative Performance AssessmentSample Preparation: Technical Approach

• Explosive material is dissolved in a solvent (methanol) and injected into a Sono-Tek Accumist ultrasonic nozzle via syringe pump

• Nozzle is stationary and motion of the deposition target (substrate) is actuated via a computer-controlled x-y stage (NEAT 300)

• Compressed air injected into the diffuser area of the nozzle– Aids in evaporation of solvent– Carries the droplets to the substrate surface

• Gravimetric analysis to determine efficiency and accuracy of method

– Results indicate a coating uniformity of 2.2%

• Conclusion: Method yields accurate and uniform explosive deposits 0.0150

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Sample

Mas

s (g

)

Al FoilAN + Foil


RDX Detection Sensitivity Measurements:Data acquired with AIRIS-WAD (8 – 11 µm coverage)


Speaker Name 10


RDX on controlled Al surfaces: Black Anodized and Polished Al Range = 5 m

• Conclusions:– RDX detection demonstrated in complex scenes at 5 m range– RDX observed at low concentrations on polished Al surface– High probability of detection (Pd > 90%) for low surface densities – No false alarm pixels

Detection of RDX Concentrations at 5 meter range

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Polished Al

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Polished Al

ITAR Information

RDX concentration (µg/cm2)


RDX on controlled Al surfaces: Black, Polished Al, and Painted SteelRange = 10 m

• Conclusions:– RDX detection demonstrated in complex scenes at 10 m range on surfaces with a

range of emissivities– No false alarm pixels


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Black Al

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Speaker Name 11


RDX on controlled Al surfaces: Black, Polished Al, and Painted SteelRange = 20 m

• Conclusions:– Detection demonstrated in complex scenes at 20 meters range – RDX observed at low concentrations on various emissivity surfaces


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Painted Steel

ITAR Information



Extended Range Detection – 37 meters

• RDX Detection– Car with Aluminum plates at 37 m standoff– 3 surface loadings on polished Aluminum


Speaker Name 12


7.5 – 10.5 µm vs. 8 – 11 µm Spectral Coverage

• Enables use of stronger absorption features• Additional spectral bands allow multi-band correlation using Automated

Target Recognition Algorithm• Conclusion:

– Expect 3x – 4x improvement in detection sensitivity with a system capable of 7.5 –10.5 micron spectral coverage

– In addition, the system would be capable of detecting HMEs

MODTRAN calculation of atmospheric transmission

- 30m range

- Boston weather

- 25C, 60% RH


• HME Detection - Urea Nitrate – UN primary IR signature below 8 microns

• Employ PAIRIS (lower performance than AIRIS-WAD, easier to modify)– Polished Aluminum Test Plates– 3 contamination loadings

• Conclusion:– Successfully demonstrated detection on all 3 concentration levels at 5 m

standoff range

HME Detections using early generation PAIRIS (7.5 – 10.5 micron spectral coverage)


Speaker Name 13


Challenges and Next Steps

• Library signature generation as a function of environmental conditions –signature robustness

• Development of next generation detection algorithms for improvedsensitivity and detection statistics (Pd and Pfa)

• Evaluation of sensor performance (ROC curves) as a function of contamination loading, range, environmental conditions, surface types, interferents, vehicle speed, etc.

– Impact on signal from surface emissivity, extent of cloud cover, and sky obscuration– Variation in sensitivity due to surface porosity, chemical permeability, and roughness

• Engineering development to align sensor with CONOPs– Adjustable FOV for increased spatial resolution at long standoff ranges– Integration with other sensors for a system of systems approach

9 cosofret standoff explosives detection using airisenergetics.chm.uri.edu/?q=system/files/9...

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