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基于知识辅助的MIMO雷达波形设计方法

关键 李秀友 黄勇 薛永华

关键, 李秀友, 黄勇, 薛永华. 基于知识辅助的MIMO雷达波形设计方法[J]. 电子与信息学报, 2016, 38(12): 3063-3069. doi: 10.11999/JEIT160008
引用本文: 关键, 李秀友, 黄勇, 薛永华. 基于知识辅助的MIMO雷达波形设计方法[J]. 电子与信息学报, 2016, 38(12): 3063-3069. doi: 10.11999/JEIT160008
GUAN Jian, LI Xiuyou, HUANG Yong, XUE Yonghua. Knowledge-aided MIMO Radar Waveform Design Method[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3063-3069. doi: 10.11999/JEIT160008
Citation: GUAN Jian, LI Xiuyou, HUANG Yong, XUE Yonghua. Knowledge-aided MIMO Radar Waveform Design Method[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3063-3069. doi: 10.11999/JEIT160008

基于知识辅助的MIMO雷达波形设计方法

doi: 10.11999/JEIT160008
基金项目: 

国家自然科学基金(61471382, 61401495, 61201445, 61179017, 61501487),山东省自然科学基金(2015ZRA06052),泰山学者建设工程专项经费

Knowledge-aided MIMO Radar Waveform Design Method

Funds: 

The National Natural Science Foundation of China (61471382, 61401495, 61201445, 61179017, 61501487), Natural Science Foundation of Shandong Province (2015ZRA 06052), Special Funds of Taishan Scholars Construction Engineering

  • 摘要: 该文针对雷达系统受到天线主瓣和副瓣杂波以及强干扰影响时性能下降问题,提出基于距离扩展目标和杂波先验信息的MIMO雷达波形设计方法。首先建立了目标函数,综合考虑了波束主瓣增益、旁瓣杂波抑制能力以及目标输出SCNR的改善性能;然后在优化问题求解中对约束条件进行松弛,使得波形矩阵空域和时域2维解耦合,从而实现空域波束形成和时域波形设计独立优化求解;其次利用L-BFGS算法设计恒模的发射波形矩阵,形成低副瓣的波束方向图和较深的强杂波抑制凹口,并基于目标输出SCNR最大化准则,利用迭代算法分步求解优化的主瓣发射波形和接收滤波器;最后通过电磁仿真的距离扩展目标数据验证所提算法的有效性。
  • VESPE M, JONES G, and BAKER C J. Lessons for radar: waveform diversity in echolocating mammals[J]. IEEE Signal Processing Magazine, 2009, 26(1): 65-75.
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出版历程
  • 收稿日期:  2016-01-04
  • 修回日期:  2016-05-30
  • 刊出日期:  2016-12-19

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