期刊文献+

虚拟子阵平滑算法 被引量:1

Virtual Subarrays Smoothing Algorithm
在线阅读 下载PDF
导出
摘要 主动阵列发射正交信号可以极大地扩展阵列的虚拟孔径,阵列的自由度成几何增长。该文利用主动阵列发射同频带时域正交PCM信号构造的虚拟子阵,提出了一种虚拟子阵平滑(VSS)算法,可解决不同目标回波信号相干的问题。该算法避免了接收阵列物理孔径的损失,当接收阵列具有M个阵元时,最大可分辨的相干数目为M?1。仿真实验表明VSS算法的有效性,而且该算法只需要较少的阵元发射信号。 The active arrays can extend the virtual aperture greatly by transmitting orthogonal signals, and degrees of freedom are increased exponentially. In this paper, By transmitting orthogonal signals , virtual subarrays are designed, and the Virtual Subarrays Smoothing(VSS) algorithm is proposed for the coherent case. Virtual subarrays with M identical sensors avoid the reduction of the array effective aperture, and make this approach estimate M - 1 coherent returns at most. Simulation results show that the VSS algorithm is effective and need only a little sensors transmitting signals.
出处 《电子与信息学报》 EI CSCD 北大核心 2009年第6期1367-1370,共4页 Journal of Electronics & Information Technology
基金 国家自然科学基金(60602022)资助课题
关键词 信号处理 主动阵列 正交信号 虚拟子阵 波达方向 Signal processing Active arrays Orthogonal signals Virtual subarrays Direction -of-arrival
  • 相关文献

参考文献9

  • 1Shan T J, Wax M, and Kailath T. On spatial smoothing for direction-of-arrival estimation of coherent signals. IEEE Trans. on ASSP, 1985, 33(8): 806-811.
  • 2Pillai S U and Kwon B H. Forward/backward spatial smoothing techniques for coherent signal identification. IEEE Trans. on ASSP, 1989, 37(1): 8-15.
  • 3叶中付,沈凤麟.基于空间差分技术的测向方法[J].电子学报,1996,24(7):38-43. 被引量:6
  • 4王布宏,王永良,陈辉.相干信源波达方向估计的加权空间平滑算法[J].通信学报,2003,24(4):31-40. 被引量:36
  • 5齐崇英,王永良,张永顺,陈辉.色噪声背景下相干信源DOA估计的空间差分平滑算法[J].电子学报,2005,33(7):1314-1318. 被引量:18
  • 6Bekkerman I and Tabrikian J. Target detection and localization using MIMO radars and sonars. IEEE Trans. on Signal Processing, 2006, 54(10): 3873-3883.
  • 7Tabrikian J and Bekkerman I. Transmission diversity smoothing for multi-target localization. ICASSP, Philadelphia, PA, 2005: 1041-1044.
  • 8Hai Deng. Polyphase code design for orthogonal netted radar systems. IEEE Trans. on Signal Processing, 2004, 52(11): 3126-3135.
  • 9Kay S M. Fundamentals of Statistical Signal Processing: Estimation Theory. Englewood Cliffs, N J: Prentice-Hall, 1993, Chapter 5.

二级参考文献27

  • 1叶中付,沈凤麟.基于空间差分技术的测向方法[J].电子学报,1996,24(7):38-43. 被引量:6
  • 2EVANS J E, JOHSON J R, SUN D F. High resolution angular spectrum estimation techniques for terrain scattering analysis and angle of arrival estimation[A]. IEEE 1st ASSP workshop spectral estimation Canada[C]. 1981. 134-139.
  • 3EVANS J E, JOHSON J R, SUN D F. Application of Advanced Signal Processing Techniques to Angle of Arrival Estimation in ACT Navigation and Surveillance System[R]. M I T Lincoln Lab, Lexington, MA, Tech Rep, 582, June 1982.
  • 4SHAN T J, WAX M, KAILATH T. On spatial smoothing for direction -of -arrival estimation of coherent signals[J]. IEEE Trans on ASSP, 1985, 33(4):806-811.
  • 5PILLAI S U, KWON B H. Forward-backward spatial smoothing techniques for the coherent signal identification[J]. IEEE Trans on ASSP, 1989, 37(1): 8-15.
  • 6WILLIAMS R T, PRASAD S, MAHALANABIS A K. An improved spatial smoothing technique for beating estimation in a multipath environment[J]. IEEE Trans on ASSP, 1988, 36(4): 425-432.
  • 7JIAN L I. Improved angular resolution for spatial smoothing techniques[Y]. IEEE Trans on SP, 1992, 40(12):3078-3081.
  • 8WEIXIU D, KIRLIN R. Improved spatial smoothing techniques for DOA estimation of coherent signals[Y]. IEEE Trans on SP, 1991,39 (5):1208-1210.
  • 9GRENIER D, BOSSE E. Decorrelation performance of DEESE and spatial smoothing techniques for direction-of-arrival problems[J].IEEE Trans on SP, 1996, 44 (6):1579-1584.
  • 10WAX M, KAILATH T. Detection of signals by information theoretic criteria[J]. IEEE Trans on ASSP, 1985, 33 (2):387-392.

共引文献54

同被引文献11

  • 1何子述,韩春林,刘波.MIMO雷达概念及其技术特点分析[J].电子学报,2005,33(B12):2441-2445. 被引量:97
  • 2FISHLER E, HAIMOVICH A, BLUM R S, et al. MIMO radar= an idea whose time has come[C]// Proceedings of the IEEE Conference on Radar. Philadelphia, Pennsylvania: IEEE Press, 2004:71-78.
  • 3BEKKERMAN I, TABRIKIAN J. Target detection and localization using MIMO radars and sonars[J]. IEEE Trans on Signal Processing, 2006, 54 (10): 3873 3883.
  • 4STOICA P, LI J, XIE Y. On probing signal design for MIMO radar[J]. IEEE Trans on Signal Processing, 2007, 55(8): 4151-4161.
  • 5LEHMANN N H, HAIMOVICH A M, Bitma R S, et al. High resolution capabilities of MIMO radar [C]// 14th Asilomar Conference on Signals, Systems and Computers (ACSSC ' 06), Conference Record. Pacific Grove, CA: IEEE Press, 2006: 25-30.
  • 6CHEN D F, CHEN B X, QI G D. Angle estimation using ESPRIT in MIMO radar[J]. Electronics Letters, 2008, 44(12).. 770-771.
  • 7XIE W, HE Z S. Multiple-target localization and estimation of MIMO radars with unknown transmitted signals[J]. IEEE International Symposium on Signal Processing and Information Technology, 2008, 3009-3012.
  • 8TABRIKIAN J, BEKKERMAN I. Transmission diversity smoothing for multitarget localization[C]// Proc. ICASSP05, 2005, 4: 1041-1044.
  • 9LI J, STOICA P. MIMO radar signal processing [D]. Hoboken: John Wiley & Sons, Inc. 2009.
  • 10STOICA P, MOSES R L. Spectral analysis of signals[M]. Upper Saddle River: Prentice-Hall, 1997,.

引证文献1

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