基于多级嵌套维纳滤波自适应对角加载STAP算法

Adaptive diagonal loading STAP arithmetic based on multistage nested Wiener filter

针对小快拍情况下的空时自适应处理(STAP)算法滤波性能下降,提出了基于多级嵌套维纳滤波(MSNWF)的自适应对角加载算法。算法充分利用MSNWF给出的干扰和噪声特征值信息,在分析MSNWF后向迭代实现过程基础上,推导出能递推实现的等价的自适应对角加载算法。通过在后向迭代过程中自适应选择加载量,增加稍许运算量的同时,较大程度地提高了空时自适应处理算法的滤波性能。仿真结果验证了算法的有效性。

To solve the problem of space-time adaptive processing（STAP） performance degradation due to small sample support,a novel method of adaptive diagonal loading based on multistage nested Wiener filter（MSNWF） is proposed.The method offers an equivalent solution of diagonal loading via recursion based on the analysis of MSNWF backward recursion by making full use of the interference and noise eigenvalue information provided by MSNWF forward recursion.The diagonal loading factor is adaptively adjusted in backward recursion.Analysis and results of the experiment show that the proposed method enhances the performance of STAP with a little more computational burden.