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一种基于盲分离的欺骗干扰抑制算法 被引量:29

An Algorithm of Deception Jamming Suppression Based on Blind Signal Separation
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摘要 该文针对单天线雷达的欺骗干扰,研究了一种基于盲分离的欺骗干扰抑制方法。该方法在对接收信号进行分段提取的基础上,借助特征矩阵联合对角化(JADE)的盲分离技术获得多段分离信号,然后利用分选技术获取完整源信号,最后根据数字射频存储技术(DRFM)的相位量化特性鉴别目标和干扰。仿真结果表明,在高信噪比(SNR)下算法对欺骗干扰具有较好的抑制性能,且当SNR>15 dB时,目标回波相似系数大于85%;相位量化位数低于4位时,鉴别概率接近100%,目标延迟时间测量误差小于0.3μs。 This paper presents a suppression method based on Blind Signal Separation (BSS) to counter deception jamming in the single channel. First, the received signal is cut into 3 sections. Next, the mixed one is separated into two parts by the Joint Approximate Diagonalization of Eigenmatrices (JADE) BSS technology. Then, those 4 parts are combined with each other to form two complete signals, namely, echo and deception jamming. Finally, the target and deception jamming are identified by the character of phase quantization. The experiments validate the effectiveness of the proposed algorithm. This approach has good performance under high SNR. When SNR〉 15 dB, the similarity coefficient of target echo is larger than 85%. Under the condition of 4 quantization bits, the probability of identification is almost close to 1 and the measurement error of target delay is below 0.3 μs.
作者 罗双才 唐斌
出处 《电子与信息学报》 EI CSCD 北大核心 2011年第12期2801-2806,共6页 Journal of Electronics & Information Technology
基金 国家部委基金资助课题
关键词 信号处理 数字射频存储技术 欺骗干扰抑制 特征矩阵联合对角化(JADE)盲分离 Signal processing Digital radio frequency memory Deception jamming suppression JointApproximate Diagonalization of Eigenmatrices (JADE) blind signal separation
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参考文献13

  • 1Greco M, Gini F, and Farina. A. Radar detection and classification of jamming signals belonging to a cone class. IEEE Transactions on Signal Processing, 2008, 56(5): 1984-1993.
  • 2Lu Gang, Zeng De-guo, and Tang Bin. Anti-jamming filtering for DRFM repeat jammer based on stretch processing. 2010 2nd International Conference on Signal Processing Systems(ICSPS), Dalian, 2010, Vol. 1: 78-82.
  • 3王建明,伍光新,周伟光.盲源分离在雷达抗主瓣干扰中的应用研究[J].现代雷达,2010,32(10):46-49. 被引量:60
  • 4黄健喜,计征宇,黄顺吉.基于ICA的主、被动雷达抗干扰性能研究[J].信号处理,2007,23(1):15-18. 被引量:6
  • 5肖文书,张兴敢,都思丹.雷达信号的盲分离[J].南京大学学报(自然科学版),2006,42(1):38-43. 被引量:25
  • 6Fevotte C and Godsill S J, A Bayesian approach for blind separation of sparse sources. IEEE Transactions on Audio, Speech, and Language Processing, 2006, 14(6): 2174-2188.
  • 7Hopgood J R and Rayner P J W. Single channel nonstationary stochastic signal separation using linear time-varying filters. IEEE Transactions on Signal Processing, 2003, 51(7): 1739-1752.
  • 8Warner E S and Proudler I K. Single-channel blind signal separation of filtered MPSK signals. IEE Proceedings on Radar, Sonar & Navigation, 2003, 150(6): 396-402.
  • 9陈晓军,成昊,唐斌.基于ICA的雷达信号欠定盲分离算法[J].电子与信息学报,2010,32(4):919-924. 被引量:23
  • 10Hao C, Tang Bin, Du Jing-jing, et al.. Single channel pulse train radar signal separation using algebraic method. 2009 IET International in Radar Conference, Guilin, 2009: 1-4.

二级参考文献34

  • 1张贤达,保铮.盲信号分离[J].电子学报,2001,29(z1):1766-1771. 被引量:210
  • 2肖文书,张兴敢,都思丹.雷达信号的盲分离[J].南京大学学报(自然科学版),2006,42(1):38-43. 被引量:25
  • 3刘宏伟,张守宏,廖桂生.一种基于信号谱自相关特性的盲波束形成方法[J].西安电子科技大学学报,1997,24(1):58-65. 被引量:3
  • 4Hyvainen A. Fast and robust algorithm for independent component analysis. IEEE Transactions of Neural Network, 1999, 10 (5) : 626 - 634.
  • 5Hyvainen A, Oja E. A fast fixed-point algorithm for independent component analysis. Neural Computation, 1997, 9:1 483 - 1 492.
  • 6Bell A J, Sejnowski T J. An information - maximization approach to blind separation and blind deconvolution. Neural Computation, 1995, 7 ( 6 ) :1 004-1 034.
  • 7Comm P. Independent component analysis, anew concept. Signal Processing, 1994,36- 287 -314.
  • 8Papadias C B, Paulraj A. A Constant modulus algorithm for multi-user signal separation in presence of delay spread using antenna arrays. IEEE Signal Processing Letters, 1997,4(7) : 178 - 181.
  • 9Aissa-EI-Bey, Linh-Trung N, and Abed-Meraim K, et al.. Underdetermined blind separation of nondisjoint sources in the time-frequency domain. IEEE Transactions on Signal Processing, 2007, 55(3): 897-907.
  • 10Delorme A, Sejnowski T, and Makeig S. Enhanced detection of artifacts in EEG data using high-order statistics and independent component analysis[J]. Neuroimage, 2007, 34(4) 1443-1449.

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