Pierre Lahaie

Effect of growth media and washing on the spectral signatures of aerosolized biological simulants

We have evaluated the influence of growth media and washing on the laser-induced fluorescence spectra of bacteria. Three different bacterial simulants were cultured in three types of growth media. Three kinds of samples were generated from each culture: the culture itself, the growth medium alone, and a triple-washed sample. The materials were injected as aerosols in a lab-sized lidar aerosol chamber to obtain their spectra. Using two different analysis approaches, signature variations were observed between the three kinds of samples for most combinations of growth media/bacteria. This study concludes that the culture media used influences the spectral signatures.

Bioaerosols laser-induced fluorescence provides specific robust signatures for standoff detection

One of todays primary security challenges is the emerging biological threat due to the increased accessibility to biological warfare technology and the limited efficiency of detection against such menace. At the end of the 90s, Defence R&D Canada developed a standoff bioaerosol sensor, SINBAHD, based on intensified range-gated spectrometric detection of Laser Induced Fluorescence (LIF) with an excitation at 351 nm. This LIDAR system generates specific spectrally wide fluorescence signals originating from inelastic interactions with complex molecules forming the building blocks of most bioaerosols. This LIF signal is spectrally collected by a combination of a dispersive element and a range-gated ICCD that limits the spectral information within a selected atmospheric cell. The system can detect and classify bioaerosols in real-time, with the help of a data exploitation process based on a least-square fit of the acquired fluorescence signal by a linear combination of normalized spectral signatures. The detection and classification processes are hence directly dependant on the accuracy of these signatures to represent the intrinsic fluorescence of bioaerosols and their discrepancy. Comparisons of spectral signatures acquired at Suffield in 2001 and at Dugway in 2005 of bioaerosol simulants, Bacillius subtilis var globiggi (BG) and Erwinia herbicola (EH), having different origin, preparation protocol and/or dissemination modes, has been made and demonstrates the robustness of the obtained spectral signatures in these particular cases. Specific spectral signatures and their minimum detectable concentrations for different simulants/interferents obtained at the Joint Biological Standoff Detection System (JBSDS) increment II field demonstration trial, Dugway Proving Ground (DPG) in June 2005, are also presented.

Airborne infrared-hyperspectral mapping for detection of gaseous and solid targets

Airborne hyperspectral ground mapping is being used in an ever-increasing extent for numerous applications in the military, geology and environmental fields. The different regions of the electromagnetic spectrum help produce information of differing nature. The visible, near-infrared and short-wave infrared radiation (400 nm to 2.5 μm) has been mostly used to analyze reflected solar light, while the mid-wave (3 to 5 μm) and long-wave (8 to 12 μm or thermal) infrared senses the self-emission of molecules directly, enabling the acquisition of data during night time. The Telops Hyper-Cam is a rugged and compact infrared hyperspectral imager based on the Fourier-transform technology. It has been used on the ground in several field campaigns, including the demonstration of standoff chemical agent detection. More recently, the Hyper-Cam has been integrated into an airplane to provide airborne measurement capabilities. The technology offers fine spectral resolution (up to 0.25 cm-1) and high accuracy radiometric calibration (better than 1 degree Celsius). Furthermore, the spectral resolution, spatial resolution, swath width, integration time and sensitivity are all flexible parameters that can be selected and optimized to best address the specific objectives of each mission. The system performance and a few measurements have been presented in previous publications. This paper focuses on analyzing additional measurements in which detection of fertilizer and Freon gas has been demonstrated.

Airborne measurements in the infrared using FTIR-based imaging hyperspectral sensors

Hyperspectral ground mapping is being used in an ever-increasing extent for numerous applications in the military, geology and environmental fields. The different regions of the electromagnetic spectrum help produce information of differing nature. The visible, near-infrared and short-wave infrared radiation (400 nm to 2.5 μm) has been mostly used to analyze reflected solar light, while the mid-wave (3 to 5 μm) and long-wave (8 to 12 μm or thermal) infrared senses the self-emission of molecules directly, enabling the acquisition of data during night time. Push-broom dispersive sensors have been typically used for airborne hyperspectral mapping. However, extending the spectral range towards the mid-wave and long-wave infrared brings performance limitations due to the self emission of the sensor itself. The Fourier-transform spectrometer technology has been extensively used in the infrared spectral range due to its high transmittance as well as throughput and multiplex advantages, thereby reducing the sensor self-emission problem. Telops has developed the Hyper-Cam, a rugged and compact infrared hyperspectral imager. The Hyper-Cam is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides passive signature measurement capability, with up to 320x256 pixels at spectral resolutions of up to 0.25 cm-1. The Hyper-Cam has been used on the ground in several field campaigns, including the demonstration of standoff chemical agent detection. More recently, the Hyper-Cam has been integrated into an airplane to provide airborne measurement capabilities. A special pointing module was designed to compensate for airplane attitude and forward motion. To our knowledge, the Hyper-Cam is the first commercial airborne hyperspectral imaging sensor based on Fourier-transform infrared technology. The first airborne measurements and some preliminary performance criteria for the Hyper-Cam are presented in this paper.

Bioaerosol Standoff Monitoring Using Intensified Range-Gated Laser-Induced Fluorescence Spectroscopy

The biological aerosol threat has become a major military and civilian security challenge, primarily due to the increased accessibility to biological technologies, and perhaps partially due to technical difficulties in developing effective detection systems. Defence Research and Development Canada (DRDC) has investigated various technologies, including point and standoff systems for environmental aerosol monitoring, to enhance readiness for such threats. Standoff bio-aerosol systems were based on infrared techniques and laser-induced fluorescence (LIF) approaches. These LIDAR systems were designed to monitor the atmosphere from a standoff position, measuring light scatter or fluorescence signals originating from particle-based biological molecules. In the case of LIF, the signal is spectrally resolved by a combination of grating elements and a range-gated intensified charge couple device (ICCD) that records the spectral information within a range-selected atmospheric volume. Multivariate data analysis techniques may be used to achieve real time detection. Advanced data processing techniques combined with the sensitive sensor have demonstrated the potential to detect and discriminate a mixture of several biological species. Instrument detection limits were determined to be within the target range specified for military and civilian scenarios. The potential of this innovative sensor to measure spectral data of various biological agent simulants, interferants and ambient bio-aerosols of natural and anthropogenic origins will be discussed. The detection limits obtained with this new sensor during open air releases for several given materials, cloud depths and ranges were assessed.

Evaluation of adaptive algorithms for detection and classification of fluorescent aerosols in the atmosphere

Photon counting technologies are developed and could be used in the future to measure the return from laser induced fluorescence. Currently, the spectral detection of light emitted by fluorescing aerosols is performed with ICCD, Intensified Charge Coupled Device. The signal to noise ratio of ICCD devices is smaller by a factor of √2compared to photon counting devices having the same sensitivity. We studied the impact of this difference of signal to noise ratio on the capability of multivariate detection and classification algorithms to operate on various conditions. Signal simulations have been performed to obtain ROC (Receiver Operation Characteristics) Curves and Confusion Matrix to obtain the detection performance and the ability of algorithms to discriminate a potential source from another. Two detection algorithms are used, the Integrated Laser Induced Fluorescence(ILIF) and the Matched Filter. For the classification, three algorithms are used, the Adaptive Matched Filter (AMF), the Adaptive Coherent Estimator (ACE) and the Adaptive Least Squares (ALS). The best algorithm for detection is the AMF using the signature of the material present in a cloud, the ILIF detector performs very well. For the classification, the three algorithms are surprisingly giving the same results for the same data. The classification performs better if the distance between the signatures recorded in a database is important. The performance of the detector and of the classificator improves with an increase of the signal to noise ratio and is consistently and significantly better for the photon counting compared to ICCD.

Standoff detection of bioaerosols over wide area using a newly developed sensor combining a cloud mapper and a spectrometric LIF lidar

A standoff sensor called BioSense was developed to demonstrate the capacity to map, track and classify bioaerosol clouds from a distant range and over wide area. The concept of the system is based on a two steps dynamic surveillance: 1) cloud detection using an infrared (IR) scanning cloud mapper and 2) cloud classification based on a staring ultraviolet (UV) Laser Induced Fluorescence (LIF) interrogation. The system can be operated either in an automatic surveillance mode or using manual intervention. The automatic surveillance operation includes several steps: mission planning, sensor deployment, background monitoring, surveillance, cloud detection, classification and finally alarm generation based on the classification result. One of the main challenges is the classification step which relies on a spectrally resolved UV LIF signature library. The construction of this library relies currently on in-chamber releases of various materials that are simultaneously characterized with the standoff sensor and referenced with point sensors such as Aerodynamic Particle Sizer® (APS). The system was tested at three different locations in order to evaluate its capacity to operate in diverse types of surroundings and various environmental conditions. The system showed generally good performances even though the troubleshooting of the system was not completed before initiating the Test and Evaluation (T&E) process. The standoff system performances appeared to be highly dependent on the type of challenges, on the climatic conditions and on the period of day. The real-time results combined with the experience acquired during the 2012 T & E allowed to identify future ameliorations and investigation avenues.

BioSense/SR-BioSpectra demonstrations of wide area/early warning for bioaerosol threats: program description and early test and evaluation results

Threats associated with bioaerosol weapons have been around for several decades and have been mostly associated with terrorist activities or rogue nations. Up to the turn of the millennium, defence concepts against such menaces relied mainly on point or in-situ detection technologies. Over the last 10 years, significant efforts have been deployed by multiple countries to supplement the limited spatial coverage of a network of one or more point bio-detectors using lidar technology. The addition of such technology makes it possible to detect within seconds suspect aerosol clouds over area of several tens of square kilometers and track their trajectories. These additional capabilities are paramount in directing presumptive ID missions, mapping hazardous areas, establishing efficient counter-measures and supporting subsequent forensic investigations. In order to develop such capabilities, Defence Research and Development Canada (DRDC) and the Chemical, Biological, Radiological-Nuclear, and Explosives Research and Technology Initiative (CRTI) have supported two major demonstrations based on spectrally resolved Laser Induced Fluorescence (LIF) lidar: BioSense, aimed at defence military missions in wide open spaces, and SR-BioSpectra, aimed at surveillance of enclosed or semienclosed wide spaces common to defence and public security missions. This article first reviews briefly the modeling behind these demonstration concepts. Second, the lidar-adapted and the benchtop bioaerosol LIF chambers (BSL1), developed to challenge the constructed detection systems and to accelerate the population of the library of spectral LIF properties of bioaerosols and interferents of interest, will be described. Next, the most recent test and evaluation (T&E) results obtained with SR-BioSpectra and BioSense are reported. Finally, a brief discussion stating the way ahead for a complete defence suite is provided.

Classification and anomaly detection algorithms for weak hyperspectral signal processing

In applications involving weak light signal like hyperspectral or time distributed signals obtained in applications involving laser induced fluorescence spectral detection, fluorescence lifetime imaging, Raman Spectroscopy or hyperspectral imaging in low light environment, the photons arrive at such a rate that they can be counted or have to be intensified to obtain a usable signal. Detection and classification algorithms need to be designed and evaluated for weak hyperspectral signal processing. A new algorithm, Adaptive Shot Noise (ASN) based on the assumption that a signal respects the Poisson multivariate distribution has been developed using the method of the maximum likelihood. This algorithm demonstrates the capability to be used for detection and classification. Using Monte Carlo simulations its performances are compared with the Adaptive Coherence Estimator (ACE) classification and with an Integrated Signal Algorithm (ISA) and ACE for detection. This new algorithm provides a small increase in performance compared to ACE in very weak signal conditions for classification and in some conditions better performance over both ACE and ISA in detection. The algorithm behavior like ACE shows sensitivity to assumption on the spectral characteristics of the source for the detection, which is not the case for ISA.

Detection of unexploded ordnance using airborne LWIR emissivity signatures

This paper investigated the potential of using LWIR spectral emissivity signatures to detect unexploded ordnance in the impact ranges of the Canadian Forces Bases. The experimental setup was composed of inert projectiles of various sizes and coating, and various potential false alarm objects. LWIR Hypercam images were acquired at 30 minutes intervals between 9:30 on Aug 23 and 21h00 on Aug 24 2013 from a height of 20m at nadir. Images were processed to emissivity and the Generalized Likelihood Ratio Test (GLRT) was used to perform the detection. Results show that the GLRT is suitable for detecting the paint used to cover the projectiles if they are not covered by vegetation. Other detected targets, such as glass and wood, are spectrally distinct and would not appear as false alarms.