复杂地形环境下基于CL-KA-STAP的低空风切变风速估计方法

Wind Speed Estimation Method of Low-altitude Wind Shear Based on CL-KA-STAP in Complex Terrain Environment

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,地杂波呈现的非均匀特征导致难以准确获得杂波统计特性,进而影响杂波抑制效果,使得风切变风速估计不准的问题,该文提出一种色加载知识辅助STAP(CL-KA-STAP)的低空风切变风速估计方法。该方法首先构造降维联合时空变换矩阵,并对待检测距离单元的回波信号进行降维处理,然后将由数字高程模型(DEM)和国家土地覆盖数据库(NLCD)获取的先验知识融入到组合空时主通道自适应处理器(CMCAP)中,构造色加载系数优化函数求解色加载系数,最后构造滤波器,实现杂波自适应滤波并准确估计风速。后续仿真结果证明了所提方法的有效性。

When the airborne weather radar detects low-altitude wind shear in a complex terrain environment,the non-uniform characteristics of ground clutter make it difficult to accurately obtain clutter statistical characteristics,which in turn affects the clutter suppression effect,and makes the wind speed estimation of wind shear inaccurate.A Colored-Loading Knowledge-Aided STAP(CL-KA-STAP)wind speed estimation method of low-altitude wind shear is proposed.This method first constructs a dimensionality reduction joint space-time transformation matrix,and performs dimensionality reduction processing on the echo signal of the distance unit to be detected,and then integrates the prior knowledge obtained by the Digital Elevation Model(DEM)and the National Land Cover Database(NLCD)into the combined space.In the Combined space-time Main Channel Adaptive Processor(CMCAP),the color loading coefficient optimization function is constructed to solve the color loading coefficient,and finally the filter is constructed to realize the adaptive filtering of clutter and accurately estimate the wind speed.The subsequent simulation results prove the effectiveness of the proposed method.