基于非线性最小二乘的机载气象雷达回波谱矩估计方法

机载气象雷达无法检测雷达回波信噪比（signal to noise ratio, SNR）很低的晴空湍流和干性风切变。提出了一种参数化的机载气象雷达回波谱矩估计方法，该方法利用非线性最小二乘(nonlinear least squares, NLS)方法拟合回波的自相关序列估计谱矩。引入循环优化思想来解决多个高斯谱回波混合时的谱矩估计问题。给出了将谱矩估计的二维搜索问题转化为两个一维搜索的快速算法。理论和仿真实验与分析表明，提出的方法适用于信噪比较低的情况。

Nonlinear least-squares spectral moment estimation algorithm

The clear air turbulence and the dry windshear cannot be effectively detected by the airborne weather radar because of the low signal-to-noise ratio (SNR). A parametric spectral moment estimation method is proposed, which is based on a nonlinear least squares (NLS) fit of the autocorrelation sequence of the radar echoes. And the relaxation-based method is used to solve the NLS problem when the echoes are mixed up with several echoes with Gaussian shaped spectrum. Also, a fast algorithm is given, which substitutes the 2D-search with a two 1D-search. Finally, theoretical and numerical simulation results are presented to verify the performances. It is demonstrated that the presented method is effective in low SNR.