吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (3): 973-980.doi: 10.13229/j.cnki.jdxbgxb201703039

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Linear shrinkage-based blind target detection for MIMO radar with large arrys

JIANG Hong, LI Yin, LYU Wei   

  1. College of Communication Engineering, Jilin University, Changchun 130012, China
  • Received:2016-04-21 Online:2017-05-20 Published:2017-05-20

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Abstract: Aiming at Multiple Input Multiple Output (MIMO) radar system with large arrays, in which the number of arrays is comparable to the number of snapshots, a blind target detection method based on Linear Shrinkage-Standard Condition Number (LS-SCN) is proposed by combining the shrinkage algorithm of Covariance Matrix estimation and the large dimensional random matrix theory. By solving the optimization of the sample CM in the large dimensional regime and utilizing the M-P law, the relationship between the detection threshold and the shrinkage coefficient is derived. Single-target and multi-target detection algorithms based on LS-SCN are presented respectively. The method is not sensitive to noise changes and is suitable for large array system, which do not need to know the priori information of noise variance, target scattering matrix and target location. Simulation results show that, compared with SCN algorithm and Minimum Description Length (MDL) algorithm, the proposed methods significantly improve the performance of target detection under the circumstance that the numbers of arrays and snapshots grow at the same rate.

Key words: communications, radar engineering, target detection, large-dimensional random matrix theory, shrinkage algorithm, large arrays

CLC Number: 

  • TN911.23
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