Bogdan R. Cosofret

Imaging sensor constellation for tomographic chemical cloud mapping.

A sensor constellation capable of determining the location and detailed concentration distribution of chemical warfare agent simulant clouds has been developed and demonstrated on government test ranges. The constellation is based on the use of standoff passive multispectral infrared imaging sensors to make column density measurements through the chemical cloud from two or more locations around its periphery. A computed tomography inversion method is employed to produce a 3D concentration profile of the cloud from the 2D line density measurements. We discuss the theoretical basis of the approach and present results of recent field experiments where controlled releases of chemical warfare agent simulants were simultaneously viewed by three chemical imaging sensors. Systematic investigations of the algorithm using synthetic data indicate that for complex functions, 3D reconstruction errors are less than 20% even in the case of a limited three-sensor measurement network. Field data results demonstrate the capability of the constellation to determine 3D concentration profiles that account for ~?86%? of the total known mass of material released.

AIRIS standoff multispectral sensor

The AIRIS Wide Area Detector is an imaging multispectral sensor that has been successfully tested in both ground and airborne configurations for the detection of chemical and biological agent simulants. The sensor is based on the use of a Fabry-Perot based tunable filter with a 256x256 pixel HgCdTe focal plane array providing a 32x32 degree field of regard with 10 meter spatial resolution at a range of 5 km. The sensor includes a real-time processor that produces an infrared image of the scene under interrogation overlaid with color-coded pixels indicating the identity and location of simulants detected by the sensor. We review test data from this sensor taken at Dstl Porton Down, NSWC Dahlgren, as well as from multiple test entries at Dugway Proving Ground. The data indicate the ability to detect release quantities from 0.15 to 360 kg at ranges of ~ 4.7 km including simultaneous multi-simulant releases.

Utilization of advanced clutter suppression algorithms for improved standoff detection and identification of radionuclide threats

Technology development efforts seek to increase the capability of detection systems in low Signal-to-Noise regimes encountered in both portal and urban detection applications. We have recently demonstrated significant performance enhancement in existing Advanced Spectroscopic Portals (ASP), Standoff Radiation Detection Systems (SORDS) and handheld isotope identifiers through the use of new advanced detection and identification algorithms. The Poisson Clutter Split (PCS) algorithm is a novel approach for radiological background estimation that improves the detection and discrimination capability of medium resolution detectors. The algorithm processes energy spectra and performs clutter suppression, yielding de-noised gamma-ray spectra that enable significant enhancements in detection and identification of low activity threats with spectral target recognition algorithms. The performance is achievable at the short integration times (0.5 – 1 second) necessary for operation in a high throughput and dynamic environment. PCS has been integrated with ASP, SORDS and RIID units and evaluated in field trials. We present a quantitative analysis of algorithm performance against data collected by a range of systems in several cluttered environments (urban and containerized) with embedded check sources. We show that the algorithm achieves a high probability of detection/identification with low false alarm rates under low SNR regimes. For example, utilizing only 4 out of 12 NaI detectors currently available within an ASP unit, PCS processing demonstrated Pd,ID > 90% at a CFAR (Constant False Alarm Rate) of 1 in 1000 occupancies against weak activity (7 - 8μCi) and shielded sources traveling through the portal at 30 mph. This vehicle speed is a factor of 6 higher than was previously possible and results in significant increase in system throughput and overall performance.

Development of the Virtual Source Training Toolkit for physically accurate simulation of the response of handheld radiation detectors

Law enforcement officers and public safety personnel are a critical component of the Global Nuclear Detection Architecture, and would benefit from additional opportunities to train for this mission in realistic threat scenarios. Physical Sciences Inc. (PSI) is developing a Virtual Source Training Toolkit (VSTT) system capable of reproducing the response of handheld radiation detectors to a virtual source in a complex occlusion and shielding environment. The toolkit will allow additional low-cost training opportunities for these officers inside operationally relevant public areas in order to reduce the time required to detect and localize a realistic radiological threat. The main components of the VSTT are a user position estimation system and a radiation propagation algorithm. Both algorithms operate at 10 Hz update rate on a handheld Android smart device that simulates the user interface of a radiation detector. The user position and orientation are determined through a Bayesian fusion process between the smart phone IMU measurements and range estimates to Bluetooth beacons. The radiation propagation algorithm simulates both attenuation and scattering of radiation between the programmed virtual source position and the user’s estimated position. The VSTT has been demonstrated to provide an average localization error < 1.2 m while traversing a complex interior space including walls and magnetic perturbations. The simulated radiation spectra achieve Spectral Angle Mapping values < 0.93 between simulated and measured source configurations through multiple shielding materials and thicknesses. In a series of experiments, an operator is able to rapidly localize a virtual source using a prototype VSTT.

Advanced LWIR hyperspectral sensor for on-the-move proximal detection of liquid/solid contaminants on surfaces

Sensor technologies capable of detecting low vapor pressure liquid surface contaminants, as well as solids, in a noncontact fashion while on-the-move continues to be an important need for the U.S. Army. In this paper, we discuss the development of a long-wave infrared (LWIR, 8-10.5 μm) spatial heterodyne spectrometer coupled with an LWIR illuminator and an automated detection algorithm for detection of surface contaminants from a moving vehicle. The system is designed to detect surface contaminants by repetitively collecting LWIR reflectance spectra of the ground. Detection and identification of surface contaminants is based on spectral correlation of the measured LWIR ground reflectance spectra with high fidelity library spectra and the system’s cumulative binary detection response from the sampled ground. We present the concepts of the detection algorithm through a discussion of the system signal model. In addition, we present reflectance spectra of surfaces contaminated with a liquid CWA simulant, triethyl phosphate (TEP), and a solid simulant, acetaminophen acquired while the sensor was stationary and on-the-move. Surfaces included CARC painted steel, asphalt, concrete, and sand. The data collected was analyzed to determine the probability of detecting 800 μm diameter contaminant particles at a 0.5 g/m2 areal density with the SHSCAD traversing a surface.

QCL-based standoff and proximal chemical detectors

The development of two longwave infrared quantum cascade laser (QCL) based surface contaminant detection platforms supporting government programs will be discussed. The detection platforms utilize reflectance spectroscopy with application to optically thick and thin materials including solid and liquid phase chemical warfare agents, toxic industrial chemicals and materials, and explosives. Operation at standoff (10s of m) and proximal (1 m) ranges will be reviewed with consideration given to the spectral signatures contained in the specular and diffusely reflected components of the signal. The platforms comprise two variants: Variant 1 employs a spectrally tunable QCL source with a broadband imaging detector, and Variant 2 employs an ensemble of broadband QCLs with a spectrally selective detector. Each variant employs a version of the Adaptive Cosine Estimator for detection and discrimination in high clutter environments. Detection limits of 5 μg/cm2 have been achieved through speckle reduction methods enabling detector noise limited performance. Design considerations for QCL-based standoff and proximal surface contaminant detectors are discussed with specific emphasis on speckle-mitigated and detector noise limited performance sufficient for accurate detection and discrimination regardless of the surface coverage morphology or underlying surface reflectivity. Prototype sensors and developmental test results will be reviewed for a range of application scenarios. Future development and transition plans for the QCL-based surface detector platforms are discussed.

Man-portable radiation detector based on advanced source detection, identification, and localization algorithms

The search and identification of radioactive sources using man-portable radiation detectors is an essential part of the mission carried out by first responders, law enforcement and military personnel. Current approaches use ad-hoc techniques based on the experiences and training of individual users and suffer from low repeatability and long localization times. A systematic approach can significantly enhance the search capability by implementing the best search practices aided by processing algorithms embedded on ubiquitous mobile computing devices. In this paper we report on the performance results of the IDtector™ hand-held radiation detection system developed by Physical Sciences Inc. (PSI). The system combines real-time (1 Hz) threat detection and isotope identification with advanced search techniques for source localization in a compact and flexible package. The system is evaluated in the context of a wide-area search for a radioactive source. The use of PSIs Poisson Clutter Split (PCS) algorithm implemented on the system results in detection and simultaneous identification of a nominal 1 mCi source from 15 m stand-off range, while operating at a mission relevant false warning rate of 1 in 4 hrs. Source localization is facilitated by a Spin-to-Locate (STL) technique which uses shielding by the operators body to modulate the radiation flux and estimate source azimuth. STL can be employed immediately following detection and results in <; 15° RMS error of azimuth estimation.

Longwave infrared compressive hyperspectral imager

Physical Sciences Inc. (PSI) is developing a longwave infrared (LWIR) compressive sensing hyperspectral imager (CS HSI) based on a single pixel architecture for standoff vapor phase plume detection. The sensor employs novel use of a high throughput stationary interferometer and a digital micromirror device (DMD) converted for LWIR operation in place of the traditional cooled LWIR focal plane array. The CS HSI represents a substantial cost reduction over the state of the art in LWIR HSI instruments. Radiometric improvements for using the DMD in the LWIR spectral range have been identified and implemented. In addition, CS measurement and sparsity bases specifically tailored to the CS HSI instrument and chemical plume imaging have been developed and validated using LWIR hyperspectral image streams of chemical plumes. These bases enable comparable statistics to detection based on uncompressed data. In this paper, we present a system model predicting the overall performance of the CS HSI system. Results from a breadboard build and test validating the system model are reported. In addition, the measurement and sparsity basis work demonstrating the plume detection on compressed hyperspectral images is presented.

Dynamic 3-D chemical agent cloud mapping using a sensor constellation deployed on mobile platforms

The need for standoff detection technology to provide early Chem-Bio (CB) threat warning is well documented. Much of the information obtained by a single passive sensor is limited to bearing and angular extent of the threat cloud. In order to obtain absolute geo-location, range to threat, 3-D extent and detailed composition of the chemical threat, fusion of information from multiple passive sensors is needed. A capability that provides on-the-move chemical cloud characterization is key to the development of real-time Battlespace Awareness. We have developed, implemented and tested algorithms and hardware to perform the fusion of information obtained from two mobile LWIR passive hyperspectral sensors. The implementation of the capability is driven by current Nuclear, Biological and Chemical Reconnaissance Vehicle operational tactics and represents a mission focused alternative of the already demonstrated 5-sensor static Range Test Validation System (RTVS).1 The new capability consists of hardware for sensor pointing and attitude information which is made available for streaming and aggregation as part of the data fusion process for threat characterization. Cloud information is generated using 2-sensor data ingested into a suite of triangulation and tomographic reconstruction algorithms. The approaches are amenable to using a limited number of viewing projections and unfavorable sensor geometries resulting from mobile operation. In this paper we describe the system architecture and present an analysis of results obtained during the initial testing of the system at Dugway Proving Ground during BioWeek 2013.

Measurements and modeling of LWIR spectral emissivity of contaminated quartz sand

The fundamental understanding of effects of liquid contaminants on the longwave infrared spectral emissivity of surfaces contaminated is desirable. This research describes modeling and longwave infrared spectral emissivity measurements for samples of SiO2 (sand) with and without 0.3% (by weight) of SF96 (poly dimethyl siloxane) oil. Two different sand particle size ranges were considered. The modeling was performed using a microscattering code and the empirical emissivity measurements were made outdoors using a D&P Instruments Model 102F MicroFTIR non-imaging spectrometer. The data were calibrated and processed to retrieve the spectral emissivity. General observations included a significant increase in emissivity in the 8 to 9 and 12.5 to 13 micron regions due to the presence of the SF96. The comparison between the modeled and measured emissivities shows a consistent trend and significant separability between the spectral emissivity of sand with and without the SF96 present.