International Journal of High Speed Electronics and Systems

Threats associated with bioaerosol weapons have been around for several decades. However, with the recent political developments that changed the image and dynamics of the international order and security, the visibility and importance of these bioaerosol threats have considerably increased. Over the last few years, Defence Research and Development Canada has investigated the spectrometric LIDAR-based standoff bioaerosol detection technique to address this menace. This technique has the advantages of rapidly monitoring the atmosphere over wide areas without physical intrusions and reporting an approaching threat before it reaches sensitive sites. However, it has the disadvantages of providing a quality of information that degrades as a function of range and bioaerosol concentration. In order to determine the importance of these disadvantages, Canada initiated in 1999 the SINBAHD (Standoff Integrated Bioaerosol Active Hyperspectral Detection) project investigating the standoff detection and characterization of threatening biological clouds by Laser-Induced Fluorescence (LIF) and intensified range-gated spectrometric detection techniques. This article reports an overview of the different lessons learned with this program. Finally, the BioSense project, a Technology Demonstration Program aiming at the next generation of wide area standoff bioaerosol sensing, mapping, tracking and classifying systems, is introduced.

A Computed Tomographic Imagining Spectrometer (CTIS) is an imaging spectrometer system that acquires all the information required to reconstruct the data cube in a single integration time. This is compared to conventional systems such as whiskbroom systems, pushbroom systems, and filter wheel systems that requiring scanning in one or more coordinate direction.

CTIS systems have been designed and tested in several different singular spectral bands as well as a dual band system. In addition to hyperspectral imaging spectrometers, CTIS systems have been used as an imaging spectropolarimeter and as a ranging imaging spectrometer. An imaging spectropolarimeter not only reconstructs the spectral content at every point in the scene of interest, but also provides the Stokes parameters at every point. So instead of just one data cube, we get four data cubes, one for each element of the Stokes vector. The ranging CTIS incorporates a LADAR system with the CTIS to provide the range information to targets in scene as well as the reconstructed data cube.

The physical principles behind the CTIS system are presented as well as some of representative data from single band systems, the dual band proof of concept, the spectropolarimeter, and the ranging imaging spectrometer.

A visible, hyperspectral imager using chromotomography CT) has been built, with the goal of extending the technology to spatially extended sources with quickly varying (> 10 Hz) features, such as bomb detonations and muzzle flashes. Even with a low dispersion, ~0.7 mrad/nm, direct vision prism with undeviated wavelength near λ = 548 nm, spectral resolution of better than Δ λ < 10 nm across the λ = 400 – 600 nm band is demonstrated with spatial resolution of better than 0.5 mm. The primary objective of this paper is to show empirically that the spatial and spectral resolution of data obtained by a simple CT instrument is unchanged in projection space and reconstructed object space.

Region-of-interest cueing by hyperspectral imaging systems for tactical reconnaissance has emphasized wide area coverage, low false alarm rates, and the search for manmade objects. Because they often appear embedded in complex environments and can exhibit large intrinsic spectral variability, these targets usually cannot be characterized by consistent signatures that might facilitate the detection process. Template matching techniques that focus on distinctive and persistent absorption features, such as those characterizing gases or liquids, prove ineffectual for most hard-body targets. High-performance autonomous detection requires instead the integration of limited and uncertain signature knowledge with a statistical approach. Effective techniques devised in this way using Gaussian models have transitioned to fielded systems. These first-generation algorithms are described here, along with heuristic modifications that have proven beneficial. Higher-performance Gaussian-based algorithms are also described, but sensitivity to parameter selection can prove problematical. Finally, a next-generation parameter-free non-Gaussian method is outlined whose performance compares favorably with the best Gaussian methods.

The Defence Research and Development Canada Agency has successfully completed a Technology Demonstration Program to assess the military utility of airborne hyperspectral Imagery. This required developing a sensor, the Airborne Infrared Imaging Spectrometer (AIRIS), and collecting in-flight imagery data. AIRIS was designed as a flexible instrument using a Fourier Transform spectrometer with a spectral resolution ranging from 1 to 16 cm⁻¹, wide spectral coverage (2 to 12 microns), and different optical configurations. This paper provides a description of AIRIS and discusses examples of the spectral images collected during one air-trial. Emphasis is put on images of sub-pixel targets. Processing AIRIS data is labor intensive and can only be performed during post-trial analysis. Hardware and software modifications to AIRIS will implement a real-time processing capability over the next three years. These modifications will enable the instrument to output radiometrically calibrated digital spectrograms. These spectrograms will then be processed in real-time to output target detection and identification for selected target types.

ATK Mission Research will describe a very high speed FT-IR spectrometer that collects 1000 interferograms per second at a 4 cm⁻¹ resolution in the 2-5 micrometer bandpass. The field of view of the instrument is about 1 degree. Collection of photons is on a single cryo-cooled InSb detector with output data streamed to a RAID device for later processing. The system uses a rotating lightweight air bearing mirror to achieve rapid variation of optical path length. Tilt compensation optics include a corner cube in a variation of the Michelson arrangement. The instrument is a one-man portable, tripod-mounted unit with off-unit data collection electronics. The system is designed for field deployment where measurements of energetic events are desired. Applications are commercial and military.

Multi-color narrow-band Salisbury Screen and Jaumann Absorbers combined with optimized thick Si₃N₄ support layers are designed for wavelength selectivity in 7~14µm wavelength band. The Jaumann Absorbers are adopted as a vertically ‘stacked’ pixel structure to save space and enhance resolution compared against ‘tiled’ structure (pixels lying in a common plane).

A data fusion-based, multisensory detection system, called “Volume Sensor”, was developed under the Advanced Damage Countermeasures (ADC) portion of the US Navy's Future Naval Capabilities program (FNC) to meet reduced manning goals. A diverse group of sensing modalities was chosen to provide an automated damage control monitoring capability that could be constructed at a relatively low cost and also easily integrated into existing ship infrastructure. Volume Sensor employs an efficient, scalable, and adaptable design framework that can serve as a template for heterogeneous sensor network integration for situational awareness. In the development of Volume Sensor, a number of challenges were addressed and met with solutions that are applicable to heterogeneous sensor networks of any type. These solutions include: 1) a uniform, but general format for encapsulating sensor data, 2) a communications protocol for the transfer of sensor data and command and control of networked sensor systems, 3) the development of event specific data fusion algorithms, and 4) the design and implementation of modular and scalable system architecture. In full-scale testing on a shipboard environment, two prototype Volume Sensor systems demonstrated the capability to provide highly accurate and timely situational awareness regarding damage control events while simultaneously imparting a negligible footprint on the ship's 100 Mbps Ethernet network and maintaining smooth and reliable operation in a real-time fashion.

The Inexpensive Chemical Agent Detection System (ICADS) consists of a network of affordable line-of-sight sensors, each designed to detect chemical threats passing between two points with high sensitivity and a low false-alarm rate. Each leg of the ICADS system is composed of two devices, a broadband IR transmitter, and a receiver containing a long-wave-IR spectrometer. The spectrometer continually measures the spectrum of the radiation emitted by the transmitter, which is separated from the receiver by up to several hundred meters, forming a line of protection. A chemical vapor or aerosol plume with sufficient long-wave-IR absorption causes a characteristic change in the spectrum of light collected by the receiver as the plume crosses the protected line, signaling a threat. Background measurements were conducted to determine background-limited performance. Additionally, a sensor composed of a long-wave-IR fixed-grating spectrometer and a hot-filament transmitter was designed and built. Measurements of the signal-to-noise ratio (SNR) and resolution agree with our analytical model and meet sensor requirements.

To address the problem of sources and sinks of atmospheric CO₂, measurements are needed on a global scale. Satellite instruments show promise, but typically measure the total column. Since sources and sinks at the surface represent a small perturbation to the total column, a precision of better than 1% is required. No species has ever been measured from space at this level. Over the last three years, we have developed a small instrument based upon a Fabry-Perot interferometer that is highly sensitive to atmospheric CO₂. We have tested this instrument in a ground based configuration and from aircraft platforms simulating operation from a satellite. The instrument is characterized by high signal to noise ratio, fast response and great specificity. We have performed simulations and instrument designs for systems to detect, H₂O, CO, ¹³CO₂, CH₄, CH₂O, NH₃, SO₂, N₂O, NO₂, and O₃. The high resolution and throughput, and small size of this instrument make it adaptable to many other atmospheric species. We present results and discuss ways this instrument can be used for ground, aircraft or space based surveillance and the detection of pollutants, toxics and industrial effluents in a variety of scenarios including battlefields, industrial monitoring, or pollution transport.

Background scene characterization in the long wave infrared (LWIR) region of the electromagnetic spectrum is of particular interest for simulating the operational environment of passive standoff chemical detection systems. In conjunction with collections of local metrological data and temperature and water vapor profiles, spectrally resolved LWIR imagery, acquired using a scanned Fourier Transform Spectrometer, and boresighted visible imagery were collected during Fall 2005. Resulting spectra in the 700 – 1450 cm⁻¹ frequency range were analyzed to provide estimates of the foreground/background temperature differential that can then be used as a metric to assess the information content in the resulting IR imagery. Measurements were performed at two geographical sites and over 100 GBs of raw data were accumulated. Through spatio-temporal analysis of the resulting temperature differential maps, we have derived strategies for optimizing scan patterns. These optimized strategies attempt to minimize the amount of redundant data thus providing shorter inter-sample times for temporally varying portions of the scene. Considerations include the first and second order spatial and temporal statistics as well as information content as quantified by average pixel entropy. This research was financed by the U.S. Army Joint Project Manager for Nuclear, Biological, and Chemical Contamination Avoidance under contract number N00024-03-D-6606.

This paper presents comparative analysis of different wavelength ranges for the spectroscopic detection of acetone vapor. We collected and analyzed original absorption line spectra arising from electronic transitions in the ultraviolet, near-infrared vibrational overtones, mid-infrared fundamentals, THz torsional modes, and mm-wave rotational transitions. Peak absorption cross sections of prominent spectral features are determined. The relative merit of each spectral range for sensing is considered, taking into account the absorption strength, available technology, and possible interferences.

Standoff LIDAR detection of BW agents depends on accurate knowledge of the infrared and ultraviolet optical elastic scatter (ES) and ultraviolet fluorescence (UVF) signatures of bio-agents and interferents. MIT Lincoln Laboratory has developed the Standoff Aerosol Active Signature Testbed (SAAST) for measuring polarization-dependent ES cross sections from aerosol samples at all angles including 180° (direct backscatter) [1]. Measurements of interest include the dependence of the ES and UVF signatures on several spore production parameters including growth medium, sporulation protocol, washing protocol, fluidizing additives, and degree of aggregation. Using SAAST, we have made measurements of the polarization-dependent ES signature of Bacillus globigii (atropheaus, Bg) spores grown under different growth methods. We have also investigated one common interferent (Arizona Test Dust). Future samples will include pollen and diesel exhaust. This paper presents the details of the apparatus along with the results of recent measurements.

Heavy loads of aerosols in the air have considerable health effects in individuals who suffer from chronic breathing difficulties. This problem is more acute in the Middle-East, where dust storms in winter and spring transverse from the neighboring deserts into dense populated areas. Discrimination between the dust types and association with their source can assist in assessment of the expected health effects. A method is introduced to characterize the properties of dense dust clouds with passive IR spectral measurements. First, we introduce a model based on the solution of the appropriate radiative transfer equations. Model predictions are presented and discussed. Actual field measurements of silicone-oil aerosol clouds with an IR spectro-radiometer are analyzed and compared with the theoretical model predictions. Silicone-oil aerosol clouds have been used instead of dust in our research, since they are composed of one compound in the form of spherical droplets and their release is easily controlled and repetitive. Both the theoretical model and the experimental results clearly show that discrimination between different dust types using IR spectral measurements is feasible. The dependence of this technique on measurement conditions, its limitations, and the future work needed for its practical application of this technique is discussed.

Remote sensing of chemical warfare agents (CWA) with stand-off hyperspectral sensors has a wide range of civilian and military applications. These sensors exploit the spectral changes in the ambient photon flux produced thermal emission or absorption after passage through a region containing the CWA cloud. In this work we focus on (a) staring single-pixel sensors that sample their field of view at regular intervals of time to produce a time series of spectra and (b) scanning single or multiple pixel sensors that sample their FOV as they scan. The main objective of signal processing algorithms is to determine if and when a CWA enters the FOV of the sensor.

We shall first develop and evaluate algorithms for staring sensors following two different approaches. First, we will assume that no threat information is available and we design an adaptive anomaly detection algorithm to detect a statistically-significant change in the observed spectrum. The algorithm processes the observed spectra sequentially-in-time, estimates adaptively the background, and checks whether the next spectrum differs significantly from the background based on the Mahalanobis distance or the distance from the background subspace. In the second approach, we will assume that we know the spectral signature of the CWA and develop sequential-in-time adaptive matched filter detectors. In both cases, we assume that the sensor starts its operation before the release of the CWA; otherwise, staring at a nearby CWA-free area is required for background estimation. Experimental evaluation and comparison of the proposed algorithms is accomplished using data from a long-wave infrared (LWIR) Fourier transform spectrometer.

The construction of very good hyperspectral sensors operating in the thermal infrared bands from 8 to 12 microns arouses much interest for the development of data exploitation tools. Temperature emissivity separation (TES) algorithms are very important components of a future toolbox, because they make it possible to extract these two fundamental targets’ parameters. The emissivity relies on the nature of the target's surface materials, while the temperature gives information related to their use and relationship with the environment. The TES technique presented in this paper is based on iteration on temperature principle, where a total square error criterion is used to estimate the temperature. The complete procedure is described in the paper. Its sensitivity to noise is studied and a mathematical behavior model is provided. The model is validated through a Monte-Carlo simulation of the technique's operation.

To investigate the detection limits of biological aerosols using passive infrared measurements, we have developed a computational model that relies on physics-based simulations to generate a statistical sample. The simulation consists of three principal models: an atmospheric turbulence model, a radiative transfer model and a target detection model. The turbulence model is used to generate microscale atmospheric variability. Resulting temperature and density profiles, along with custom aerosol profiles, are used to generate inputs for MODTRAN5, which produces simulated atmospheric spectral radiance. The simulated data is then analyzed by using an optimal detection algorithm and a hypothesis test, resulting in receiver operating characteristic (ROC) curves.

The concept design and preliminary applications of a new Eye Safe Polarization Diversity Lidar (ESPDL) instrument are described. The lidar operates with polarization diversity in the laser emission and polarization discrimination in the receiver at 1574 nm for tropospheric aerosol studies in the Arctic atmosphere. This instrument was originally designed to operate in the eye-safe wavelength range with a one-channel receiver and 20 dB linear polarization accuracy in the laser emission, and assembled in a compact optical bench. The instrument was upgraded for polarization diversity laser emission, i.e polarization selectivity better than 30 dB, and for linear polarization reception discrimination, i.e. polarization discrimination better than 50 dB. Geophysical lidar applications under the scope of this instrument with an overall instrumental polarimetric accuracy better than 0.1% focus on the identification of very dilute suspended aerosols in the troposphere, ice in-cloud initiation and aerosol/water interfaces, complex aerosols, sub-visible high altitude clouds and environmental issues and dynamic processes in the Arctic such as ice fog, forest fire, and a multilayered stably stratified Arctic boundary layer. In this article we describe the instrument design concept and the electronic synchronization necessary to achieve the maximum instrumental polarization accuracy. We report a preliminary case study of differential polarization analysis.

Identification of aerosol type and chemical composition may help to trace their origin and estimate their impact on land and people. Aerosols chemical composition, size distribution and particles shape, manifest themselves in their spectral scattering cross-section. In order to make a reliable identification, comprehensive spectral analysis of aerosol scattering should be carried out. Usually, spectral LIDAR measurements of aerosols are most efficiently performed using an Nd:YAG laser transmitter in the fundamental frequency and its 2^nd, 3^rd and 4^th harmonics. In this paper we describe automatic detection and identification of several aerosol types and size distributions, using a multi-spectral lidar system operating in the IR, NIR and UV spectral regions. The LIDAR transmitter is based on a single Nd:YAG laser. In addition to the 3^rd and 4^th harmonics in the UV, two optical parametric oscillator units produce the eye-safe 1.5 µm wavelength in the near IR and up to 40 separable spectral lines in the 8-11 µm IR. The combination of a wide spectral coverage required for backscattering analysis combined with fluorescence data, enable the generation of a large spectral data set for aerosols identification. Several natural and anthropogenic aerosol types were disseminated in controlled conditions, to test system capabilities. Reliable identification of transient and continuous phenomena demands fast and efficient control and detection algorithms. System performance, using the specially designed algorithms, is described below.

The single crystal growth of KPb₂Br₅ by vertical Bridgman technique using in-house processed zone refined PbBr₂ and KBr with rare-earth terbium doping has been studied. The grown moisture resistant crystals (1.5 cm diameter and 10 cm length) have shown high promise for low phonon energy room temperature solid-state laser applications in the longer side of mid-IR (4-15 µm) due to their high storage lifetimes, wide tunability, and excellent optical quality. The processed crystals are highly transparent (T= ≥80%) in the 0.4-25 µm spectral region. Repeated melting-freezing cycles during differential scanning calorimetry (DSC) experiments did not reveal any appreciable variation in the melting point or phase transitions, which is indicative of their excellent thermal stability. The emission spectra pumped with a 2 µm source show broadband emissions with peak wavelength of 3 µm (⁷F₄→ ⁷F₆), 5µm (⁷F₅→ ⁷F₆) and 7.9µm (⁷F₄→ ⁷F₅). The KPb₂Br₅:Tb laser crystals will be highly useful for standoff detection of incoming chemical and biological threats using unique infrared absorption signatures.

We have developed a hyperspectral deconvolution algorithm that sharpens the spectral dimension in addition to the more usual across-track and along-track dimensions. Using an individual three-dimensional model for each pixel's point spread function, the algorithm iteratively applies maximum likelihood criteria to reveal previously hidden features in the spatial and spectral dimensions. Of necessity, our solution is adaptive to unreported across-track and along-track vibrations with amplitudes smaller than the ground sampling distance. We sense and correct these vibrations using a combination of maximum likelihood deconvolution and gradient descent registration that maximizes statistical correlations over many bands. Test panels in real hyperspectral imagery show significant improvement when locations are corrected. Tests on simulated imagery show that the precision of relative corrected positions improves by about a factor of two.