Target Detection Based on Canonical Correlation Technique for Large Array MIMO Radar in Spatially Correlated Noise
ID:34 View Protection:ATTENDEE Updated Time:2020-08-05 10:16:59 Hits:477 Oral Presentation

Start Time:2020-06-08 15:20(Asia/Shanghai)

Duration:20min

Session:S Special Session » SS15Integrated Radar-Communication Systems and Networks: Advancements, Challenges, and Opportunities

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Abstract
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.
Keywords
MIMO radar; target detection; canonical correlation; spatially correlated noise; Tracy-Widom law
Speaker
Meihan Zhou
Jilin University, China

Submission Author
Meihan Zhou Jilin University, China
Hong Jiang Jilin University, China
Siyan Dong Jilin University, China
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Important Date
  • Conference Date

    Jun 08

    2020

    to

    Jun 11

    2020

  • Jan 12 2020

    Draft paper submission deadline

  • Apr 15 2020

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Sponsored By
IEEE Signal Processing Society
Organized By
Zhejiang University
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