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基于阻塞预处理的多基地雷达抗主瓣干扰算法 被引量:9

Main-lobe Jamming Suppression Algorithm for Multistatic Radar Based on Block Preconditioning
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摘要 针对雷达无法对抗主瓣内伴随干扰的问题,该文研究了一种多基地雷达抗主瓣干扰的技术,提出基于阻塞预处理的自适应主瓣干扰对消算法(BP-AMJCA)。该算法首先将阻塞预处理与直接矩阵求逆法相结合,快速得到初始权向量,然后将高阶累积量引入到变遗忘因子递归最小二乘(HOC-VFF-RLS)算法中实现权值的更新。与传统基于最小均方的自适应主瓣干扰对消算法(LMS-AMJCA)相比,该算法复杂度变化不大,但收敛速度快、鲁棒性好。通过进行主瓣干扰抑制仿真实验,结果表明:采用BP-AMJCA算法有效解决了主瓣内目标回波信号被抑制的问题,使得两个接收站的输出信干噪比改善了35-40 dB,具有重要的应用价值。 For the issue that escort jamming in main-lobe can not be countered by radar, a main-lobe jamming suppression technique about multistatic radar is studied, and the Adaptive Main-lobe Jamming Cancellation Algorithm based on Block Preconditioning (BP-AMJCA) is proposed in this paper. Firstly, block preconditioning is combined with direct matrix inversion to get the initiM weight vector, then High Order Cumulants is introduced to Variable Forgetting Factor Recursive Least Square (HOC-VFF-RLS) Algorithm to realize the update of weights. Compared with traditional Adaptive Main-lobe Jamming Cancellation Algorithm based on Least Menu Square (LMS-AMJCA), the proposed Mgorithm has little complexity increase, fast convergent rate and good robustness. The simulation experiment result of main-lobe jamming suppression shows that the issue of target echo signal cancellation in main-lobe is solved, and the output SINR of two receivers is improved to 35-40 dB by BP-AMJCA algorithm, which has important application value.
出处 《电子与信息学报》 EI CSCD 北大核心 2014年第3期734-738,共5页 Journal of Electronics & Information Technology
关键词 多基地雷达信号处理 抗干扰 主瓣相消 阻塞预处理 Multistatic radar signal processing Jamming suppression Main-lobe cancellation Blockpreconditioning
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参考文献16

  • 1Vorobyov S A, Gershman A B, and Luo Z Q. Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem[J]. IEEE Transactions on Signal Processing, 2003, 51(2): 313-324. 被引量:1
  • 2Chang L and Yeh C C. Performance of DMI and eigenspace- based beamformers[J]. IEEE Transactions on Antenna Propagation, 1992, 40(11): 1336-1347. 被引量:1
  • 3刘柏君..高频雷达中基于多频信号的波束形成方法研究[D].哈尔滨工业大学,2011:
  • 4刘聪锋,杨洁,甘昶.加载与约束结合的主瓣干扰抑制方向图保形[J].电波科学学报,2012,27(2):344-349. 被引量:13
  • 5Niu Zhi-jun and Pei Bing-nan. Study on suppression of main-lobe interference in over the horizon radar[C]. 2012 IEEE International Conference on Information Science and Technoloy, Wuhan, 2012: 410-413. 被引量:1
  • 6刘红明.双基地MIMO雷达原理与理论研究[D].[博士论文],电子科技大学,2011. 被引量:1
  • 7Kong Ling-jiang, Yang Mei, and Zhao Bin. Adaptive detection for shared-spectrum multistatic radar in Gaussian clutter[C]. 2012 IEEE Radar Conference, Atlanta, 2012: 309-313. 被引量:1
  • 8黄庆东..最小模级联相消器算法研究[D].西安电子科技大学,2011:
  • 9李晶晶..基于新型变步长LMS的自适应谐波检测算法[D].南京信息工程大学,2012:
  • 10Kapil Belpatre and Mrs Bavhute M R. Comparative performance study between the time-varying LMS (TVLMS) algorithm, LMS algorithm and RLS algorithmiC]. National Conference on Innovative Paradigms in Engineering & Technology, USA, 2012: 6-10. 被引量:1

二级参考文献33

  • 1宋立众,乔晓林,吴群.一种基于极化DBF的制导雷达抗干扰方法[J].电波科学学报,2010,25(1):109-116. 被引量:5
  • 2C.F. So, S.C.Ng,S.H,Leungc.Gradient based variable forgetting factor RLS algorithm[J].Signal Processing,2003,83:1163-1175. 被引量:1
  • 3Constantin Paleologu, Jacob Benesty,Silviu Ciochina. A Robust Variable Forgetting Factor Recursive Least- Squares Algorithm for System Identification[J].IEEE Signal Processing Letters,2008,15:597-600. 被引量:1
  • 4Hadi Sadoghi Yazdi, Mehri Sadoghi Yazdi,MohammadReza Mohammadi. A Novel Forgetting Factor Recursive Least Square Algorithm Applied to the Human Motion Analysis[J].World Academy of Science, Engineering and Technology,2009,57:969-976. 被引量:1
  • 5D. J. Park,B.E. Jun. Selfperturbing Recursive Least Squares Algoritlhm with Fast Tracking Capability[J]. Electronic Letters.1992,28:558-559. 被引量:1
  • 6Kwang-Seop Eom, Byung-Eul Jun,Dong-Jo Park. Fast tracking and noise-immunised RLS algorithm based on Kalman filter[J]. Electronic Letters. 1996,3211-2312. 被引量:1
  • 7Anum Ali,Anis-ur-Rehman,Rana Liaqat Ali.An Improved Gain Vector to Enhance Convergence Characteristics of Recursive Least Squares Algorithm[J]. International Journal of Hybrid Information Technology. 2011,4:99-107. 被引量:1
  • 8西蒙·赫金泊适应滤波器原理[M].4版.北京:电子工业出版社,2010. 被引量:1
  • 9THEIL A. On combining adaptive nulling with high resolution angle estimation under main lobe interfer- ence conditions[J]. IEEE Aerospace and Electronic Systems Magazine, 1990, 5(11): 16-18. 被引量:1
  • 10HUGHES D T, MCWHIRTER J G. Using the penal- ty function to cope with mainbeam jammers[C]//The Proceesings of 3rd International Conference on Signal Processing, Beijing China, IEEE, 14 18 Oct 1996: 461-464. 被引量:1

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