一种强主瓣压制干扰环境下的雷达目标距离–角度联合稀疏估计方法

A sparse estimation algorithm for the radar target range-direction under strong mainlobe jamming conditions

提出了一种强主瓣压制干扰环境下的雷达目标距离–角度联合稀疏估计方法,目的在于有效抑制多个强主瓣压制干扰,同时提取目标的距离和空间角度信息.新方法首先将雷达天线面阵的每一行(列)接收数据进行空域自适应处理,可在一维上有效抑制多个强主瓣压制干扰,并保留另一维的目标角度信息,然后利用基于稀疏Bayes学习的距离–角度联合估计算法提取目标的距离和俯仰角(方位角)信息.新方法在系统幅相误差及频带误差所带来的干扰抑制剩余情况下同样有效,具有较强的鲁棒性.最后,通过性能分析给出了新方法对干扰与目标之间夹角、目标信噪比的适用条件.

In this paper,a sparse estimation algorithm for the radar target range and direction under strong mainlobe blanket jamming conditions is presented.This algorithm can effectively suppress multiple strong mainlobe blanket jammings (multi-MLJs)and extract the information about target distance and direction.First, the space domain adaptive processing for the received signal in each row (or column)is adopted to suppress multi-MLJs.Second,the sparse Bayesian learning is employed to obtain the information of the target distance and elevation (or azimuth).In addition,the proposed method still has an effective performance under the error condition and the applicable conditions of the new algorithm based on the performance analysis are provided in this paper.