Reduced-Rank STAP for Slow-Moving Target Detection by Antenna-Pulse Selection
Reduced-Rank STAP for Slow-Moving Target Detection by Antenna-Pulse Selection
复制标题
DOI：
10.1109/lsp.2015.2390148
复制
发表时间：
2015-01
影响因子：
3.9
通讯作者：
Xiangrong Wang;E. Aboutanios;M. Amin
中科院分区：
文献类型：
--
作者：
Xiangrong Wang;E. Aboutanios;M. Amin
空时自适应处理（STAP）是机载雷达系统杂波抑制的有效策略。有限的训练数据、高计算负载和训练数据的异构性构成了STAP的主要挑战。在这封信中，我们提出了一种新的检测策略，该策略基于选择与目标和杂波轨迹之间的最大间隔相关的天线脉冲对的最佳子集。所提出的策略减少了冗余，同时解决了检测缓慢移动目标的上述三个相互关联的挑战，特别是在异构情况下。提出了一种迭代最小-最大算法来解决天线脉冲选择问题，该算法是NP难组合优化问题。大量的仿真结果证实了所提出策略的有效性。
Space-time adaptive processing (STAP) is an effective strategy for clutter suppression in airborne radar systems. Limited training data, high computational load and the heterogeneity of training data constitute the main challenges in STAP. In this letter, we propose a new detection strategy based on selecting an optimum subset of antenna-pulse pairs associated with maximum separation between the target and the clutter trajectory. The proposed strategy reduces redundancy while addressing the above three interlinked challenges for detecting slow-moving targets especially in heterogeneous cases. An iterative Min-Max algorithm is proposed to solve the antenna-pulse selection problem, which is NP-hard combinatorial optimization. Extensive simulation results confirm the effectiveness of the proposed strategy.