针对高光谱激光雷达回波信号能量弱导致的波形信息常常淹没在噪声中而难以提取的问题, 基于高光谱激光雷达原理验证样机系统采集到的高光谱激光雷达回波信号数据, 通过分析小波变换参数选取对信号处理的影响, 寻找到一种基于小波变换的高光谱激光雷达回波微弱信号的处理方法, 即在sym6小波3层分解下, 运用软阈值函数和启发式阈值处理可有效处理高光谱激光雷达回波微弱信号, 运用该方法在仅有少量回波样本信号数量情况下, 达到高斯拟合在数倍回波样本信号数量情况下的处理效果, 降低了提取出波形信息所需要的高光谱激光雷达回波信号探测时间。

To solve the problem that the information of weak targets is often submerged in noise and difficult to extract, the hyperspectral LiDAR echo signal data collected from hyperspectral LiDAR principle verification prototype system was analyzed and the influence of wavelet transform parameters on signal processing was investigated, then a method based on wavelet transform was proposed. Simulation results show that using soft threshold function and the heuristic threshold in 3 layers decomposed sym6 wavelet can effectively process and recover the weak echo signal of hyperspectral LiDAR. Same processing effects can be achieved with Gaussian fitting method by using fewer sample signals based on this method. So the detecting time for extracting effective signals of hyperspectral LiDAR echo signal can be significantly reduced.