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We present a sequential algorithm for estimating both concentration dependence on range and time and backscatter coefficient spectral dependence of optically thin localized atmospheric aerosols using data from rapidly tuned lidar. The range dependence of the aerosol is modeled as an expansion of the concentration in an orthonormal basis set whose coefficients carry the time dependence. Two estimators are run in parallel: a Kalman filter for the concentration range and time dependence and a maximum-likelihood estimator for the aerosol backscatter wavelength and time dependence. These two estimators exchange information continuously over the data-processing stream. The state model parameters of the Kalman filter are also estimated sequentially together with the concentration and backscatter. Lidar data collected prior to the aerosol release are used to estimate the ambient lidar return. The approach is illustrated on atmospheric backscatter long-wave infrared (CO2) lidar data.

The US Army Edgewood Chemical Biological Center is the leader in development of military systems for chemical and biological defense, in collaboration with all Services, other Government laboratories, academia, and industry. Chemical and biological optical sensing principles, unique capabilities, state-of-the-art sensors, and emerging technologies will be discussed. Exciting new results will be presented on standoff biodiscrimination using infrared (IR) depolarization lidar and long-wave IR (LWIR) lidar. BACKGROUND

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