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零训练样本的集中式MIMO雷达斜对称检测器

杨海峰 蒋国喜 刘维建 谢文冲 王永良

杨海峰, 蒋国喜, 刘维建, 谢文冲, 王永良. 零训练样本的集中式MIMO雷达斜对称检测器[J]. 电子与信息学报, 2018, 40(2): 479-485. doi: 10.11999/JEIT170295
引用本文: 杨海峰, 蒋国喜, 刘维建, 谢文冲, 王永良. 零训练样本的集中式MIMO雷达斜对称检测器[J]. 电子与信息学报, 2018, 40(2): 479-485. doi: 10.11999/JEIT170295
YANG Haifeng, JIANG Guoxi, LIU Weijian, XIE Wenchong, WANG Yongliang. Persymmetric Detectors Without Training Data for Colocated MIMO Radar[J]. Journal of Electronics & Information Technology, 2018, 40(2): 479-485. doi: 10.11999/JEIT170295
Citation: YANG Haifeng, JIANG Guoxi, LIU Weijian, XIE Wenchong, WANG Yongliang. Persymmetric Detectors Without Training Data for Colocated MIMO Radar[J]. Journal of Electronics & Information Technology, 2018, 40(2): 479-485. doi: 10.11999/JEIT170295

零训练样本的集中式MIMO雷达斜对称检测器

doi: 10.11999/JEIT170295
基金项目: 

国家自然科学基金青年基金(61501505, 61501506),湖北省自然科学基金(2015CFB607)

Persymmetric Detectors Without Training Data for Colocated MIMO Radar

Funds: 

The National Natoural Science Foundation of China (61501505, 61501506), The Hubei Provincial Natural Science Foundation (2015CFB607)

  • 摘要: 传统集中式多输入多输出(MIMO)雷达自适应检测器虽然不需要训练样本即可实现目标检测,但在波形采样数较少时检测性能下降明显。该文利用集中式MIMO雷达噪声协方差矩阵的斜对称结构,基于广义似然比(Generalized Likelihood Ratio Test, GLRT)准则和Wald准则,提出了相应的斜对称检测器,并给出了统计分布特性及检测概率和虚警概率的解析表达式。仿真结果表明所提检测器在波形采样数较少时仍可获得较好的检测性能,同时证明了理论分析的正确性。
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出版历程
  • 收稿日期:  2017-04-05
  • 修回日期:  2017-11-15
  • 刊出日期:  2018-02-19

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