An adaptive segment smoothing algorithm for lidar signal
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摘要: 为了抑制米散射大气探测激光雷达回波噪声引起的信号随机波动，采用新设计的自适应分段平滑方法对信号进行平滑处理。根据激光雷达信号特性，信号有效变化幅值大于信号背景噪声波动。以背景噪声标准差的若干倍表示信号的噪声幅度。按照相邻信号幅值差与噪声幅度的对比，可以确定信号发生有效变化的位置，这些位置可以作为信号分段端点，在分段端点内用滑动平均可以实现对信号的自动分段平滑。用实测微脉冲激光雷达信号对方法进行了验证，并与常用固定分段平滑方法进行了对比。结果表明，自适应分段平滑方法可以根据信号变化的剧烈程度自动选择平滑窗口大小，在对噪声进行有效抑制的同时，避免平滑过度造成的信号畸变。Abstract: In order to suppress the random signal fluctuations caused by the echo noise of Mie scattering atmospheric probe laser radar, a new adaptive segmentation smoothing method was designed to smooth the signal. According to the characteristics of lidar signal, the effective changing amplitude of the signal is greater than the change of background noise. The amplitude of the signal noise could be expressed by several times of the standard deviation of the background noise. After comparing the amplitude difference of the adjacent signal with the noise amplitude, the effective position of signal change was determined. These positions could be recorded as the segmental endpoints of the signal. The common moving average algorithm was applied to each segment of the lidar signal. The method was examined by using the actual micro pulse lidar signal and compared by the common fixed segment algorithm. The results show that the adaptive segment smoothing method can choose the size of the smoothing window automatically according the intensity of the signal change. The noise is suppressed effectively and the signal distortion caused by excessive smooth is avoided.
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Keywords:
- atmospheric optics /
- lidar /
- smooth /
- adaptive /
- segment
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