Journal of Xidian University

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Novel algorithm for DOA estimation based on the sparse reconstruction

WEI Juan;JI Yongxiang;NIU Junru   

  1. (State Key Lab. of Integrated Service Networks, Xidian Univ., Xi'an 710071, China)
  • Received:2017-12-15 Online:2018-10-20 Published:2018-09-25


In order to improve the DOA estimation accuracy of far-field narrow-band signals with a low signal-to-noise ratio or few snapshots, a new weighted algorithm based on -norm is proposed. First, the covariance matrix of the output data of the array is generated by using the forward-backward spatial smoothing technique. Second, the cepstrum coefficient vector is constructed in the spatial spectrum function of the Modified Capon(MCapon). The weighted matrix in accordance with the weighted-norm is obtained. Finally,the SVD algorithm is used to reduce the dimensionality of the received data to obtain the model with the weighted-norm constraint based on sparse reconstruction. The algorithm makes spurious peaks in spatial spectrum suppressed, increases robustness and improves the DOA estimation performance with a low signal-to-noise ratio (SNR) or few snapshots without decorrelation processing.

Key words: direction of arrival estimation, sparse reconstruction, Capon algorithm, weighted , norm