吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (2): 485-489.doi: 10.13229/j.cnki.jdxbgxb201402033

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High resolution direction-of-arrival estimation based on a sparse representation of array covariance matrix column vectors

CHEN Jian, TIAN Ye, SUN Xiao-ying   

  1. College of Communication and Engineering, Jilin University, Changchun 130022, China
  • Received:2013-02-20 Online:2014-02-01 Published:2014-02-01

Abstract:

This paper presents two methods of high-resolution direction-of-arrival estimation based on signal sparse representation. First, a coarse-refined grid separation is created, which is used to structure the sparse representation of array covariance column vectors corresponding to overcomplete basis. Then, a removing and differencing method is employed to suppress the inference of noise. A regularized FOCUSS algorithm with lp norm constraint is applied for sparse reconstruction. Finally, the Singular Value Decomposition (SVD) is adopted to remove the singular value, which is less than the threshold to reduce complexity as well as ill-posed problem of overcomplete basis. Simulation results validate the effectiveness and robustness of the proposed method.

Key words: communication, direction of arrival (DOA), sparse reconstruction, overcomplete basis, singular value decomposition (SVD)

CLC Number: 

  • TN911.7

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