Low complexity method for wideband DOA estimation based on sparse representation using rotational signal subspace

A low complexity method for wideband direction finding based on sparse representation is proposed, which combines the rotational signal subspace (RSS) with weighted subspace fitting (WSF) to improve the performance of DOA estimation. Exploiting the result of the focusing operation, the covariance ma...

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Bibliographic Details
Published in2017 IEEE Radar Conference (RadarConf) pp. 0460 - 0463
Main Authors Yonghong Zhao, Linrang Zhang, Juan Zhang, Yumei Guo, Yabin Gu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2017
Subjects
Computational complexity
Covariance matrices
direction-of-arrival (DOA) estimation
Direction-of-arrival estimation
Estimation
Focusing
sensor array processing
sparse representation
Wideband
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Summary:A low complexity method for wideband direction finding based on sparse representation is proposed, which combines the rotational signal subspace (RSS) with weighted subspace fitting (WSF) to improve the performance of DOA estimation. Exploiting the result of the focusing operation, the covariance matrix at the focusing frequency can be obtained and used as the data for sparse recovery to get wideband DOA estimates. The WSF is employed to reduce the sensitivity to the noise and the regularization parameter is given by the asymptotic distribution of the WSF criterion. Simulations are provided to prove the efficiency and performance of the proposed method.
ISSN:2375-5318
DOI:10.1109/RADAR.2017.7944247