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22 October 1999Optimal detection and concentration estimation of vapor materials using range-resolved lidar with frequency-agile lasers
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.
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Russell E. Warren, Richard G. Vanderbeek, 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