一种机载雷达双Capon迭代空时自适应处理算法

A Double-Capon Iterative STAP Algorithm for Airborne Radar

提出了一种机载雷达基于双Capon迭代的空时自适应处理算法,该算法首先对机载数字阵列雷达合成的列子阵进行多普勒域滤波处理,然后选取与检测单元左右相邻的若干个多普勒门信号构建空域矢量和时域矢量联合的二次代价函数,进行迭代寻优处理,每步迭代中空域和时域分别进行Capon自适应处理;利用循环最小化思想讨论了算法的收敛性。计算机仿真分析表明:该方法只需4~5次迭代即可接近收敛性能,具有计算复杂度低、样本数要求低、鲁棒性好等优点。最后通过某型机载数字阵列雷达实录数据处理验证了算法的有效性。

A novel double-Capon iterative space-time adaptive processing algorithm is proposed to suppress clutter in array-Doppler domain for airborne radar. Doppler filtering operation is firstly performed on each subarray data, and then an interesting bi-quadratic cost function about the spatial and temporal filter weights is constructed to suppress the clutter and hold the target signal. The minimum point of the cost function can be found efficiently by a bi-iteration algorithm. And the convergence of the proposed algorithm is also proven by utilizing the idea of cyclic minimization. Simulation results illustrate that the algorithm can achieve good performance by 4~5 iterations and has the merits of low computation and sampling requirements and robustness to array error. Experiment results by using the measured data show the validity of the algorithm.