机载雷达级联降维空时自适应杂波抑制方法

Two-Stage Dimension-Reduced Space-Time Adaptive Clutter Suppression Algorithm for Airborne Radar

提出一种机载雷达杂波抑制的级联降维空时自适应算法,即,先对全空时两维接收数据进行预滤波处理,将杂波局域化,降低杂波自由度;然后对预处理输出的信号的相关矩阵进行子阵划分,求解低维权向量,进一步降低运算量和采样要求。理论分析和实验仿真结果表明,所提算法具有良好的收敛性能和杂波抑制能力,并且对于阵元随机幅相误差和杂波起伏具有很好的容差能力。基于实测数据的实验验证了算法的有效性和稳健性。

A two-stage dimension-reduced space-time adaptive processing（STAP）based on correlation matrix is proposed for clutter suppression and moving target detection.Firstly,to reduce the degrees of freedom of the clutter,the full dimensional space-time received data is pre-filtered.Secondly,the correlation matrix of output data after preprocessing is divided into submatrices,and further reduction of both the computational complexity and the training requirement is achieved by optimizing two low-dimensional weight vectors.Theoretical analysis and computer simulation results illustrate that the proposed method can obtain fast convergence and better clutter suppression performance.The method shows good robust performance with a small computational cost when there are clutter fluctuation and random amplitude and phase errors in array elements.Experiment results by using measured data demonstrate effectiveness and robustness of the proposed method.