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Proceedings Paper

Noise analysis of lidar backscattering signal using forward and backward Kalman filtering algorithm with generalized random walk structures
Author(s): Jialing Gao; Zunan Wu; Zhongliang Chen; Jianming Liang
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Paper Abstract

Recursive estimation of high-frequency noise in lidar backscattering signal based on forward and backward linear Kalman filtering algorithms are exploded. Using state-space techniques, the lidar aerosol backscattering signal is identified following generalized random walk (GRW) structures. Comparisons of the estimation results between different Kalman-GRW filters are given in case studies. The spectral test of the given examples show that the forward and backward Kalman filtering algorithms processing with the GRW structures low-pass filters for the smoothing of lidar data.

Paper Details

Date Published: 18 August 1998
PDF: 7 pages
Proc. SPIE 3501, Optical Remote Sensing of the Atmosphere and Clouds, (18 August 1998); doi: 10.1117/12.317727
Show Author Affiliations
Jialing Gao, City Univ. of Hong Kong (United States)
Zunan Wu, City Univ. of Hong Kong (United States)
Zhongliang Chen, City Univ. of Hong Kong (United States)
Jianming Liang, City Univ. of Hong Kong (United States)


Published in SPIE Proceedings Vol. 3501:
Optical Remote Sensing of the Atmosphere and Clouds
Jinxue Wang; Beiying Wu; Toshihiro Ogawa; Zheng-hua Guan, Editor(s)

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