机载雷达级联降维空时自适应杂波抑制方法

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。

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

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.