复杂地形环境下基于GAMP-STAP的低空风切变风速估计方法

针对机载气象雷达在复杂的地形环境下探测低空风切变时，地杂波呈现非均匀特征和难以获取足够的独立同分布(IID)样本，导致空时自适应处理(STAP)杂波抑制性能变差，使得风切变风速估计不准的问题。该文基于杂波信号稀疏特性，提出一种广义近似消息传递(GAMP)STAP方法，GAMP-STAP仅利用少量的样本在复杂地形环境下实现了风速较准确的估计。该方法首先利用杂波脊的先验信息构造稀疏字典，然后在贝叶斯框架下利用GAMP算法估计杂波幅度，恢复杂波功率谱，进而计算杂波协方差矩阵，最后构造STAP滤波器实现杂波抑制以及风切变风速估计。后续实验仿真结果证明了该方法的有效性。

Low-altitude Wind Shear Wind Speed Estimation Method Based on GAMP-STAP in Complex Terrain Environment

When airborne weather radar is used to detect low-altitude wind shear under complex terrain environment, ground clutter presents non-uniform characteristics and it is difficult to obtain enough Independent Identically Distributed (IID) samples, which affects the clutter suppression effect of Space-Time Adaptive Processing and makes the estimation of wind shear wind speed inaccurate. Based on the sparse characteristics of clutter signals, a Generalized Approximate Message Passing (GAMP) Space-Time Adaptive Processing (STAP) method is proposed in this paper. GAMP-STAP achieves accurate estimation of wind speed in complex terrain environment with only a small number of samples. Firstly, a sparse dictionary is constructed based on the prior information of the clutter ridge, then GAMP algorithm is used to estimate the clutter amplitude and recover the clutter power spectrum under the Bayesian framework, and then the clutter covariance matrix is calculated. Finally, STAP filter is constructed to achieve clutter suppression and wind shear wind speed estimation. Simulation results show the effectiveness of the proposed method.