Reduced-Rank STAP Algorithms using Joint Iterative Optimization of Filters
Reduced-Rank STAP Algorithms using Joint Iterative Optimization of Filters
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DOI：
10.1109/taes.2011.5937257
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发表时间：
2011-07
影响因子：
4.4
通讯作者：
Rui Fa;R. D. Lamare
中科院分区：
文献类型：
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作者：
Rui Fa;R. D. Lamare
提出了一种基于滤波器联合迭代优化的降秩空时自适应处理方法。所提出的方法由一组构成投影矩阵的满秩自适应滤波器和一个在滤波器组输出处操作的自适应降秩滤波器组成。我们描述的直接形式的处理器（DFP）和广义旁瓣消除器（GSC）的结构所提出的方法。自适应算法，包括随机梯度（SG），递归最小二乘（RLS），以及它们的混合算法的联合STAP方法的有效实施。所提出的算法的计算复杂度分析显示在每个快照的乘法和加法的数量。此外，所提出的方法进行凸性分析。仿真结果表明，该算法在收敛和跟踪性能上明显优于现有的降秩算法，且复杂度明显降低。
We develop a reduced-rank space-time adaptive processing (STAP) method based on joint iterative optimization of filters (JOINT) for airborne radar applications. The proposed method consists of a bank of full-rank adaptive filters, which forms the projection matrix, and an adaptive reduced-rank filter that operates at the output of the bank of filters. We describe the proposed method for both the direct-form processor (DFP) and the generalized sidelobe canceller (GSC) structures. Adaptive algorithms including the stochastic gradient (SG), the recursive least square (RLS), and their hybrid algorithms are derived for the efficient implementation of the JOINT STAP method. The computational complexity analysis of the proposed algorithms is shown in terms of the number of multiplications and additions per snapshot. Furthermore, the convexity analysis of the proposed method is carried out. Simulations for a clutter-plus-jamming suppression application show that the proposed STAP algorithm outperforms the state-of-the-art reduced-rank schemes in convergence and tracking at significantly lower complexity.