Noise analysis of lidar backscattering signal using forward and backward Kalman filtering algorithm with generalized random walk structures

Jialing Gao; Zunan Wu; Zhongliang Chen; Jianming Liang

doi:10.1117/12.317727

18 August 1998 Noise analysis of lidar backscattering signal using forward and backward Kalman filtering algorithm with generalized random walk structures

Jialing Gao, Zunan Wu, Zhongliang Chen, Jianming Liang

Author Affiliations +

Proceedings Volume 3501, Optical Remote Sensing of the Atmosphere and Clouds; (1998) https://doi.org/10.1117/12.317727
Event: Asia-Pacific Symposium on Remote Sensing of the Atmosphere, Environment, and Space, 1998, Beijing, China

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.

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Jialing Gao, Zunan Wu, Zhongliang Chen, and Jianming Liang "Noise analysis of lidar backscattering signal using forward and backward Kalman filtering algorithm with generalized random walk structures", Proc. SPIE 3501, Optical Remote Sensing of the Atmosphere and Clouds, (18 August 1998); https://doi.org/10.1117/12.317727

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KEYWORDS

Filtering (signal processing)

Electronic filtering

LIDAR

Linear filtering

Data modeling

Interference (communication)

Digital filtering

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