基于空时自适应处理的低空风切变风速估计方法

针对机载气象雷达在探测低空风切变时，有用信号会淹没在强杂波背景中的问题，该文提出一种基于空时自适应处理(STAP)的低空风切变风速估计方法。该方法首先利用空时插值原理校正机载前视阵地杂波的距离依赖性，获得多个独立同分布(IID)样本后估计地杂波协方差矩阵，然后构造适用于分布式低空风切变目标的空时自适应处理器，在自适应抑制地杂波的同时积累低空风切变信号，最终实现风场速度的精确估计。仿真结果表明，在高杂噪比、低信噪比的情况下，该方法可有效地自适应抑制地杂波并精确地估计风场速度。

Wind Speed Estimation for Low-attitude Windshear Based on Space-time Adaptive Processing

When detecting low-attitude windshear with airborne weather radar, the real signals are usually covered with strong clutter. In this paper, a novel method of low-attitude windshear speed estimation based on Space-Time Adaptive Processing (STAP) is proposed to solve the above problem. The proposed method handles the range-dependence of clutter of airborne forward looking array with space-time interpretation theory to achieve the Independent and Identically Distributed (IID) samples used in the clutter covariance matrix estimation; then the space-time adaptive processor is constructed which is applicable to a distributed low-attitude windshear target to suppress clutter and accumulate windshear signal; finally the accurate estimation of wind speed is got. The experimental results show that the proposed method can achieve a superior clutter suppression performance and an accurate wind speed estimation in high clutter-to-noise ratio and low signal-to-noise ratio.