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

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.