Abstract：
Light detection and ranging (LIDAR) is an active remote sensing system. Lidar echo signal is non-linear and non-stationary, which is often accompanied by various noises. In order to filter out the noise and extract valid signal information, a suitable method should be chosen for noise reduction. Some denoising methods are commonly used, such as the wavelet transform (WT), the empirical mode decomposition (EMD), the variational mode decomposition (VMD), and their improved algorithms. In this paper, a new denoising method named the WT-VMD joint algorithm based on the sparrow search algorithm (SSA), for lidar signal is selected by comparative experiment analysis. It is shown that this method is the most suitable one with the maximum signal-to-noise ratio (SNR), the minimum root-mean-square error (RMSE), and a relatively small indicator of smoothness when it is used in three kinds (50, 100, and 1000 pulses) of simulate lidar signals. The SNR is increased by 138.5%, 77.8% and 42.8% and the RMSE is decreased by 81.8%, 72.0% and 68.8% when being used to the three kinds of cumulative signal without pollution. Then, the SNR is increased by 83.3%, 60.4% and 24.0% and the RMSE is decreased by 70.8%, 66.0% and 50.5% when being used to the three kinds of cumulative signal with aerosol and clouds. The WT-VMD joint algorithm based on SSA is used in the denoising process for the actual lidar signal, showing extraordinary denoising effect and will improve the inversion accuracy of the lidar signal.
摘要：
光探测和测距(LIDAR)是一种主动遥感系统。激光雷达回波信号是非线性和非平稳的,通常伴随着各种噪音。为了滤除噪声,提取有效的信号信息,应选择合适的降噪方法。一些去噪方法是常用的，例如小波变换(WT)，经验模态分解(EMD)，变分模态分解(VMD)，和他们改进的算法。在本文中,基于麻雀搜索算法(SSA)的WT-VMD联合去噪算法,对激光雷达信号进行了对比实验分析。结果表明，该方法是具有最大信噪比（SNR）的最合适方法。最小均方根误差(RMSE)，以及在三种（50、100和1000脉冲）模拟激光雷达信号中使用时相对较小的平滑度指标。信噪比提高138.5%，77.8%和42.8%，RMSE下降81.8%，分别为72.0%和68.8%,用于三种累积信号无污染。然后，信噪比提高了83.3%，60.4%和24.0%，RMSE下降了70.8%，当用于气溶胶和云的三种累积信号时，分别为66.0%和50.5%。基于SSA的WT-VMD联合算法用于实际激光雷达信号的去噪过程,显著的去噪效果,提高了激光雷达信号的反演精度。
