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针对目标识别的波形优化设计方法

纠博 刘宏伟 胡利平 吴顺君

纠博, 刘宏伟, 胡利平, 吴顺君. 针对目标识别的波形优化设计方法[J]. 电子与信息学报, 2009, 31(11): 2585-2590. doi: 10.3724/SP.J.1146.2008.01400
引用本文: 纠博, 刘宏伟, 胡利平, 吴顺君. 针对目标识别的波形优化设计方法[J]. 电子与信息学报, 2009, 31(11): 2585-2590. doi: 10.3724/SP.J.1146.2008.01400
Jiu Bo, Liu Hong-wei, Hu Li-ping, Wu Shun-jun. A Method of Waveform Design for the Recognition of Radar Targets[J]. Journal of Electronics & Information Technology, 2009, 31(11): 2585-2590. doi: 10.3724/SP.J.1146.2008.01400
Citation: Jiu Bo, Liu Hong-wei, Hu Li-ping, Wu Shun-jun. A Method of Waveform Design for the Recognition of Radar Targets[J]. Journal of Electronics & Information Technology, 2009, 31(11): 2585-2590. doi: 10.3724/SP.J.1146.2008.01400

针对目标识别的波形优化设计方法

doi: 10.3724/SP.J.1146.2008.01400
基金项目: 

教育部长江学者及创新团队支持计划(IRT0645)和国家自然科学基金(60772140)资助课题

A Method of Waveform Design for the Recognition of Radar Targets

  • 摘要: 针对宽带雷达多类目标识别波形优化中的方位敏感性、距离敏感性和初相不确定性问题,该文在高斯色噪声背景下提出一种基于遗传算法和最大滑动相关分类器的波形优化方法,简称为GASC方法。该方法定义目标回波和同类模板之间的匹配系数与该目标回波和异类模板之间匹配系数的差为匹配距离,以最大化各类目标之间的匹配距离的最小值作为优化准则,并约束发射信号幅度是恒定的,然后通过遗传算法进行求解,得到优化波形信号。仿真结果表明,与现有方法相比,该方法能更好地增加各类目标之间的可分性,进而提高目标的识别性能。
  • Haykin S. Cognitive radar: A way of the future [J]. IEEESignal Processing Magazine, 2006, 23(1): 30-40.[2]Pillai S U, Oh H S, Youla D C, and Guerci J R. Optimumtransmit-receiver design in the presence of signal-dependentinterference and channel noise [J].IEEE Transactions onInformation Theory.2000, 46(2):577-584[3]Garren D A, Osborn M K, Odom A C, Goldstein J S, Pillai SU, and Guerci J R. Enhanced target detection andidentification via optimised radar transmission pulse shape[J].IEE Proceedings Radar, Sonar and Navigation.2001,148(3):130-138[4]Guerci J R and Pillai S U. Adaptive transmission radar: thenext wave [C]. National Aerospace and ElectronicsConference, 2000. Proceedings of the IEEE 2000, Dayton, OH,USA, 2000: 779-786.Guerci J R and Pillai S U. Theory and application ofoptimum transmit-receive radar [C]. Proceedings of IEEEInternational Radar Conference, Alexandria, VA, 2000:705-710.[5]Bell M R. Information theory and radar waveform design [J].IEEE Transactions on Information Theory.1993, 39(5):1578-1597[6]Leshem A, Naparstek O, and Nehorai A. Informationtheoretic adaptive radar waveform design for multipleextended targets[J]. IEEE Journal of Selected Topics inSignal Processing, 2007: 1(1): 42-55.[7]Goodman N A, Venkata P R, and Neifeld M A. Adaptivewaveform design and sequential hypothesis testing for targetrecognition with active sensors[J].IEEE Journal of SelectedTopics in Signal Processing.2007, 1(1):105-113[8]Leshem A, Naparstek O, and Nehorai A. Informationtheoretic radar waveform design for multiple targets [C].International Waveform Diversity and Design Conference.Pisa, Italy, 2007: 362-366.Jun Hyeong Bae and Goodman N A. Adaptive waveforms fortarget class discrimination [C]. International WaveformDiversity and Design Conference. Pisa, Italy, 2007: 395-399.[9]陈国良, 王熙法, 庄镇泉, 等. 遗传算法及其应用. 北京: 人民邮电出版社, 1999: 75-88.Chen Guo-liang, Wang Xi-fa, and Zhuang Zhen-quan. Geneticalgorithm and applications. Beijing: The People's Posts andTelecommunications Press, 1999: 75-88.[10]Pillai S U, Guerci J R, and Pillai S R. Joint optimal tx-rxdesign for multiple target identification problem [C]. SensorArray and Multichannel Signal Processing WorkshopProceedings, Rosslyn, Virginia, 2002: 553-556.[11]Garren D A, Osborn M K, Odom A C, and Goldstein J S.Optimal transmission pulse shape for detection andidentification with uncertain target aspect [C]. RadarConference, 2001. Proceedings of the 2001 IEEE. Atlanta,GA, USA, 2001: 123-128.
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出版历程
  • 收稿日期:  2008-11-03
  • 修回日期:  2009-03-23
  • 刊出日期:  2009-11-19

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