采用小波分析提高雷达回波检测精度的研究

The Research of Wavelet Analysis to Improve the Wind Field Measurement

非相干多普勒激光雷达能够通过大气后向散射信号反演径向风速,然而激光雷达测量的后向散射信号包含的各种噪声和干扰信号会严重影响反演精度。我们采用离散小波变换,应用双正交小波和随距离变化的阈值设定方法,对非相干多普勒激光雷达的径向风速数据进行了降噪处理,从而提高风速反演精度。通过分析均方差以及相关系数,并与现场数据比对,显示该方法能够显著降低激光雷达风速测量误差。

Incoherent Doppler wind lidar is currently the only available instrument for wind field measurement in the clear atmosphere. It is capable of obtaining 2D wind field with high spatio-temporal resolution which is essential to numerical weather forecast, atmospheric dynamics and aeronautic security. This paper focuses on the digital data processing of ocean atmosphere detection. By analyzing the lidar backscatters, the noise of signal includes background noise, electronic noise and atmospheric fluctuation and so on. Wavelet analysis is used to improve the accuracy of the wind velocity derived from lidar backscattering. The study proposes to use discrete biorthogonal wavelets with a distance-dependent threshold to denoise wind speed that has large dynamic range along the data profile.