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

机译：基于前向和后向卡尔曼滤波算法的广义随机游动结构对激光雷达后向散射信号的噪声分析

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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. !12

机译：摘要：提出了基于前向和反向线性卡尔曼滤波算法的激光雷达后向散射信号高频噪声的递归估计。使用状态空间技术，遵循广义随机游走（GRW）结构识别激光雷达气溶胶反向散射信号。在案例研究中，给出了不同Kalman-GRW滤波器之间估计结果的比较。给定示例的频谱测试表明，使用GRW结构的低通滤波器对正向和反向Kalman滤波算法进行处理，以平滑激光雷达数据。！12

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《Optical Remote Sensing of the Atmosphere and Clouds》|1998年|p.446-452|共7页
会议地点 Beijing(CN)
作者
Jialing Gao; City Univ. of Hong Kong; Kowloon; Hong Kong; Zunan Wu; City Univ. of Hong Kong; Kowloon; Hong Kong; Zhongliang Chen; City Univ. of Hong Kong; Kowloon; Hong Kong; Jianming Liang; City Univ. of Hong Kong; Kowloon; Hong Kong.;
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中图分类自动化技术、计算机技术;
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Noise analysis of lidar backscattering signal using forward and backward Kalman filtering algorithm with generalized random walk structures

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