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DOA estimation of multiple sources in sparse space with an extended array technique

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Abstract

An algorithm to improve direction of arrival (DOA) estimation accuracy with an extended sensor array in the presence of multiple coherent signal sources is proposed. The algorithm uses virtual element theory to extend the sensor array, estimates virtual element information via linear prediction and expands the array aperture in practical sense; the sparsity of the target orientation in angle space is exploited to establish an over-complete dictionary and a reception model for the array signal in sparse space; the received array data is preprocessed using singular value decomposition (SVD) method and target DOA estimation is realized by calculating the best atoms. The algorithm improves DOA estimation accuracy by extended array and uses SVD to control computational complexity effectively, which ensures the accuracy and efficiency. Computer simulation shows that the proposed algorithm is able to accurately estimate the DOA for both single-target and closely spaced multi-target cases in low signal-to-noise ratio environments, and also has excellent DOA estimation performance in the presence of multiple coherent signal sources.

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Acknowledgments

The authors thank Professor Lin Chunsheng for critical reviews. This work is partly supported by National Defense Pre-research Foundation under Grant No. 51401020503.

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Authors and Affiliations

  1. Department of Weaponry Engineering, Naval University of Engineering, Wuhan, 430033, People’s Republic of China

    Penghao Xu & Bing Yan

  2. Science and Technology on Near-Surface Detection Laboratory, Wuxi, 214035, People’s Republic of China

    Penghao Xu & Shouwei Hu

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  1. Penghao Xu
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  2. Bing Yan
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Correspondence to Shouwei Hu.

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Xu, P., Yan, B. & Hu, S. DOA estimation of multiple sources in sparse space with an extended array technique. Cluster Comput 19, 1437–1447 (2016). https://doi.org/10.1007/s10586-016-0605-6

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