Standoff lidar simulation for biological warfare agent detection, tracking, and classification

Erika Jönsson; Ove Steinvall; Ove Gustafsson; Fredrik Kullander; Per Jonsson

doi:10.1117/12.849513

5 May 2010 Standoff lidar simulation for biological warfare agent detection, tracking, and classification

Erika Jönsson, Ove Steinvall, Ove Gustafsson, Fredrik Kullander, Per Jonsson

Proceedings Volume 7665, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XI; 766509 (2010) https://doi.org/10.1117/12.849513
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

Lidar has been identified as a promising sensor for remote detection of biological warfare agents (BWA). Elastic IR lidar can be used for cloud detection at long ranges and UV laser induced fluorescence can be used for discrimination of BWA against naturally occurring aerosols. This paper will describe a simulation tool which enables the simulation of lidar for detection, tracking and classification of aerosol clouds. The cloud model was available from another project and has been integrated into the model. It takes into account the type of aerosol, type of release (plume or puff), amounts of BWA, winds, height above the ground and terrain roughness. The model input includes laser and receiver parameters for both the IR and UV channels as well as the optical parameters of the background, cloud and atmosphere. The wind and cloud conditions and terrain roughness are specified for the cloud simulation. The search area including the angular sampling resolution together with the IR laser pulse repetition frequency defines the search conditions. After cloud detection in the elastic mode, the cloud can be tracked using appropriate algorithms. In the tracking mode the classification using fluorescence spectral emission is simulated and tested using correlation against known spectra. Other methods for classification based on elastic backscatter are also discussed as well as the determination of particle concentration. The simulation estimates and displays the lidar response, cloud concentration as well as the goodness of fit for the classification using fluorescence.

Citation Download Citation

Erika Jönsson, Ove Steinvall, Ove Gustafsson, Fredrik Kullander, and Per Jonsson "Standoff lidar simulation for biological warfare agent detection, tracking, and classification", Proc. SPIE 7665, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XI, 766509 (5 May 2010); https://doi.org/10.1117/12.849513

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