System performance and modeling of a bioaerosol detection lidar sensor utilizing polarization diversity

The weaponization and dissemination of biological warfare agents (BWA) constitute a high threat to civilians and military personnel. An aerosol release, disseminated from a single point, can directly affect large areas and many people in a short time. Because of this threat real-time standoff detection of BWAs is a key requirement for national and military security. BWAs are a general class of material that can refer to spores, bacteria, toxins, or viruses. These bioaerosols have a tremendous size, shape, and chemical diversity that, at present, are not well characterized [1]. Lockheed Martin Coherent Technologies (LMCT) has developed a standoff lidar sensor with high sensitivity and robust discrimination capabilities with a size and ruggedness that is appropriate for military use. This technology utilizes multiwavelength backscatter polarization diversity to discriminate between biological threats and naturally occurring interferents such as dust, smoke, and pollen. The optical design and hardware selection of the system has been driven by performance modeling leading to an understanding of measured system sensitivity. Here we briefly discuss the challenges of standoff bioaerosol discrimination and the approach used by LMCT to overcome these challenges. We review the radiometric calculations involved in modeling direct-detection of a distributed aerosol target and methods for accurately estimating wavelength dependent plume backscatter coefficients. Key model parameters and their validation are discussed and outlined. Metrics for sensor sensitivity are defined, modeled, and compared directly to data taken at Dugway Proving Ground, UT in 2008. Sensor sensitivity is modeled to predict performance changes between day and night operation and in various challenging environmental conditions.