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  • 胡进峰,李健萍,林涛. 一种基于稀疏降维的STAP方法[J]. 雷达科学与技术, 2019, 17(4): 421-425.    [点击复制]
  • HU Jinfeng,LI Jianping,LIN Tao. A STAP Method Based on Sparsely Reduced-Dimension[J]. Radar Science and Technology, 2019, 17(4): 421-425.   [点击复制]
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一种基于稀疏降维的STAP方法
胡进峰,李健萍,林涛
0
(1.电子科技大学信息与通信工程学院,四川成都611731;2.北京机电工程研究所,北京100074;3.复杂系统控制与智能协同技术重点实验室,北京100074)
摘要:
目前降维的空时自适应处理(STAP)运算量大,并且辅助通道选取比较固定。针对该问题,提出了一种基于稀疏降维的STAP方法。该方法首先用传统的方法选择与待检测角度-多普勒通道邻近的多个通道作为辅助通道,实现初步降维。然后,基于天波雷达的海杂波信号具有低秩特点,提出进一步用稀疏滤波优选训练样本的方法,该方法基于稀疏正则化原理,寻找稀疏的滤波权向量,从而自适应地选择性能更好的辅助通道。对天波雷达实测数据的处理结果表明,与已有的降维STAP相比,所提方法的杂波抑制性能提高了6.17dB。
关键词:  空时自适应处理  稀疏  降维  杂波抑制
DOI:DOI:10.3969/j.issn.1672-2337.2019.04.011
基金项目:国家自然科学基金(No.61671137,61731006);四川省科技厅项目(No.2017GZ0345);国防基础研究基金(No.A0420132102)
A STAP Method Based on Sparsely Reduced-Dimension
HU Jinfeng,LI Jianping,LIN Tao
(1.School of Information and Communication Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China;2.Beijing Electro-Mechanical Engineering Institute,Beijing 100074,China;3.Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory,Beijing 100074,Chin)
Abstract:
The existing reduced-dimension space-time adaptive processing (STAP) needs large computational complexity and the selection of secondary channel is fixed. To address these problems,a STAP method based on sparsely reduced-dimension is proposed in this paper. First,the proposed method selects several channels adjacent to the angle-Doppler channel under test as secondary channels,which can achieve initially reduced-dimension. Then,a method of selecting secondary channels with sparse filtering is further proposed based on the low rank property of the sea clutter of sky-wave radar. The method selects the sparsely filter weight vector based on the principle of sparse regularization,thereby adaptively chooses the better secondary channels. The simulation results of the measured data from sky-wave radar show that the clutter suppression performance of the proposed method is 6.17dB higher than the existing method.
Key words:  space-time adaptive processing (STAP)  sparse  reduced-dimension  clutter suppression