激光雷达能见度回波信号去噪算法

激光雷达能见度仪是探测大气能见度的有效手段,但其回波信号微弱且易受各种噪声干扰。抑制背景噪声并从中提取有用信号,对提高能见度反演精度十分重要。采用经验模态分解算法对回波信号进行分解及重构,达到了良好的去噪效果。仿真试验表明,经验模态分解算法有效提高了回波信号的输出信噪比,降低了测量值的均方根误差。通过处理晴天、阴天、雾天等不同天气条件下的多组实测数据,将其反演结果与大气透射仪LT31的测量结果进行对比,进一步验证了该算法的有效性。

Denoising Algorithm of Lidar Visibility Return Signals

The Lidar visibility meter is an effective means to detect atmospheric visibility, but its return signals are weak and easy to be interfered by various noises. In order to improve the accuracy of visibility inversion, the suppressing background noise and extracting useful signals from it are very important. The empirical mode decomposition algorithm is used to decompose and reconstruct the return signals, which achieves good denoising effect. The simulation results show that the empirical mode decomposition algorithm improves the output signal noise rate of return signals effectively and reduces the root mean square error. By processing several groups of measured data under different weather conditions, such as sunny, cloudy, and fog days, the inversion results are compared with the measurement results of atmospheric transmittance LT31, which further verifies the effectiveness of the algorithm.