Optimal detection and concentration estimation of vapor materials using range-resolved lidar with frequency-agile lasers

Russell E. Warren; Richard G. Vanderbeek; Francis M. D'Amico

doi:10.1117/12.366430

22 October 1999 Optimal detection and concentration estimation of vapor materials using range-resolved lidar with frequency-agile lasers

Russell E. Warren, Richard G. Vanderbeek, Francis M. D'Amico

Author Affiliations +

Proceedings Volume 3757, Application of Lidar to Current Atmospheric Topics III; (1999) https://doi.org/10.1117/12.366430
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

In previous work, we presented a methodology for optimally processing data from lidar with frequency-agile wavelength capability using techniques of multivariate statistics. Among the applications considered was the case of range- resolved lidar with short (delta function) transmitter pulses. This paper extends that analysis by deriving a method for estimating range-dependent vapor concentration for arbitrary pulse shapes. A Bayesian statistical approach leads to a MAP (maximum a posteriori) estimator for C(z), the concentration at range z. The estimates are computed iteratively for a given set of multiwavelength lidar return data using an approximation to the Gauss-Newton method. The concentration estimates are then used as the basis for a detection algorithm for the leading edge of the vapor plume based on the CUSUM approach. The detection and estimation approaches are illustrated on a combination of synthetic and field test data collected by SBCCOM at the Idaho National Engineering and Environmental Laboratory test site.

Citation Download Citation

Russell E. Warren, Richard G. Vanderbeek, and Francis M. D'Amico "Optimal detection and concentration estimation of vapor materials using range-resolved lidar with frequency-agile lasers", Proc. SPIE 3757, Application of Lidar to Current Atmospheric Topics III, (22 October 1999); https://doi.org/10.1117/12.366430

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