Target Detection Based on Canonical Correlation Technique for Large Array MIMO Radar in Spatially Correlated Noise
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报告开始:2020年06月08日 15:20(Asia/Shanghai)

报告时间:20min

所在会场:[S] Special Session [SS15] Integrated Radar-Communication Systems and Networks: Advancements, Challenges, and Opportunities

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摘要
A novel target detection algorithm for large array multi-input multi-output (MIMO) radar in spatially correlated noise is proposed in this paper based on canonical correlation technique (CCT). In the signal model, two separate sub-arrays are employed as the receiving array of a transmit diversity MIMO radar system. Assume that the elementary noise in each sub-array has spatial correlation, and the number of receiving elements is large and grows as the same rate with the snapshots. The detection statistics is constructed based on the generalized likelihood ratio test (GLRT) criterion and canonical correlation factors between two sub-arrays, and the expression of decision threshold is derived via the second distribution of Tracy-Widom law in random matrix theory. The simulation results show that the detection performance of the proposed algorithm is better than that of the conventional condition number (CN)-based algorithm in the presence of spatially correlated noise and large array.
关键词
MIMO radar; target detection; canonical correlation; spatially correlated noise; Tracy-Widom law
报告人
Meihan Zhou
Jilin University, China

稿件作者
Meihan Zhou Jilin University, China
Hong Jiang Jilin University, China
Siyan Dong Jilin University, China
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重要日期
  • 会议日期

    06月08日

    2020

    06月11日

    2020

  • 01月12日 2020

    初稿截稿日期

  • 04月15日 2020

    提前注册日期

  • 12月31日 2020

    注册截止日期

主办单位
IEEE Signal Processing Society
承办单位
Zhejiang University
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