期刊文献+

盲分离算法在MIMO雷达和通信中的应用研究 被引量:4

Blind Source Separation Algorithm in MIMO Radar and Communication Application
在线阅读 下载PDF
导出
摘要 将盲分离算法应用于多输入多输出(MIMO)雷达抗干扰和MIMO通信符号检测中。首先,利用信号相互之间以及与干扰之间的独立性,通过盲源分离算法,将各个信号分离出来;然后,雷达中通过匹配处理,完成信号检测;通信中利用少量的训练序列完成信号的匹配以及相位和幅度的校正。仿真结果表明:无论在雷达或通信中,均可获得优良的性能。 In this paper, blind source separation algorithm is applied to realize electronic counter-countermeasure of multi-input multi-output (MIMO) radars and symbol detection of MIMO communication systems. First, signals are separated by using mutual dependence among signals and between signal and interference. In radar application, signals can be detected through matching process ; while in communication application, some training sequences can be utilized to conduct signal matching and phase/amplitude correction. Simulation results show: this proposed algorithm has excellent performance in beth radar and communication systems.
作者 周万幸
出处 《现代雷达》 CSCD 北大核心 2011年第2期1-4,共4页 Modern Radar
关键词 多输入多输出 抗干扰 盲源分离 MIMO ECCM blind source separation
  • 相关文献

参考文献5

  • 1Foschini G J, Gans M J. On limits of wireless communications in a fading environment when using multiple antennas [ J ]. Wireless Personnal Communications, 1998,6 ( 3 ) : 311 - 335.
  • 2Skolnik M. Improvements for air-surveillance radar[ C ] // IEEE Radar Conference. Waltaham, MA: IEEE Press, 1999:18 -21.
  • 3Foschini G J. Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas [ J ]. Bell Labs Technical Journal, 1996,1 (2) :41 -59.
  • 4Cardoso J F, Souloumiac A. Blind beamforming for non- Gaussian signals [ J ].IEE Proceedings of Radar and Signal Processing, 1993,140 (6) :362 - 370.
  • 5Golden G D, Foschini C J, Valenzuela R A, et al. Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture [ J ]. Electronics Letters, 1999,135 ( 1 ) : 14 - 16.

同被引文献25

  • 1阙渭焰,彭应宁.一种针对有向目标的雷达优化布站方法[J].现代雷达,1996,18(6):1-7. 被引量:14
  • 2Fisher E, Haimovich A, Blum R S, et al. MIMO radar: an idea whose time has come [ C ]// Proceedings of the IEEE Radar Conference. [ S. 1. ] : IEEE Press, 2004: 71-78.
  • 3Fishier E, Haimovich A, Blum R S, et al. Performance of MIMO radar systems : Advantes of angular diversity [ C ]// 38th Asilomar Conference Signals, Systems and Computer Pacific Grove, CA: IEEE Press, 2004: 305-309.
  • 4Lehmann N H, Haimovich A, Blum R S, et al. High reso- lution capabilities of MIMO radar[ C ]//40th Asilomar Con- ference Signals, Systems and Computer. Pacific Grove, CA: IEEE Press, 2006: 25-30.
  • 5Fishier E, Haimovich A, Blum R S, et al. Spatial diversity in radars-models and detection performance [ J ]. IEEE Transac- tions on Signal Processing, 2006, 54(3) : 823-837.
  • 6Aittomaki T, Koivunen V. Target detection and positioning in correlated scattering using widely distributed MIMO radar [ C ]//Proceedings of the 7th European Radar Conference. Paris : IEEE Press. 2010 : 403-406.
  • 7Godrich H, Haimovich A, Blum R S. Cramer rao bound on target localization estimation in MIMO radar systems [ C ]// 42nd Annual Conference on Information, Science and Sys- tems. IS. 1. ] : IEEE Press, 2008: 134-139.
  • 8Chen W J, Narayanan R M. Antenna placement for minimi- zing target localization error in UWB MIMO noise radar[J]. IEEE Antennas and Wireless Propagation Letters, 2011, 10 (6) : 135-138.
  • 9He Q, Blum R S. Performance and complexity issues in noncoherent and coherent MIMO radar[ C l//43rd Asilomar Conference on Signal, Systems and Computers [ S. 1. ] : IEEE Press, 2009: 1206-1210.
  • 10He Q, Blum R S, Godrich H, et al. Target velocity estima- tion and antenna placement for MIMO radar with widely sep- arated antennas [ J ]. IEEE Transactions on Signal Process- ing, 2010, g(1) : 79-100.

引证文献4

二级引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部