Kalman-filter-based algorithm for detection and discrimination of aerosols with range-resolved frequency-agile lidar data

Richard G. Vanderbeek; Russell E. Warren

doi:10.1117/12.450900

27 November 2002 Kalman-filter-based algorithm for detection and discrimination of aerosols with range-resolved frequency-agile lidar data

Richard G. Vanderbeek, Russell E. Warren

Author Affiliations +

Proceedings Volume 4789, Algorithms and Systems for Optical Information Processing VI; (2002) https://doi.org/10.1117/12.450900
Event: International Symposium on Optical Science and Technology, 2002, Seattle, WA, United States

Abstract

A Kalman Filter based algorithm capable of detecting and discriminating one or more aerosol clouds as a function of range will be presented. The traditional Differential Scattering (DISC) technique does not optimally utilize all the information available with tunable LIDAR sensors. For this reason, the authors have investigated an alternative approach that can better handle the general multi-material multi-wavelength scenario. The processing is developed around a statistical signal model that includes additive noise and the effect of a finite laser pulse duration. This algorithm was tested using data that was generated to simulate the response of the Army's FAL sensor. The algorithm is shown to be able discriminate between three materials.

Citation Download Citation

Richard G. Vanderbeek and Russell E. Warren "Kalman-filter-based algorithm for detection and discrimination of aerosols with range-resolved frequency-agile lidar data", Proc. SPIE 4789, Algorithms and Systems for Optical Information Processing VI, (27 November 2002); https://doi.org/10.1117/12.450900

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