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Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013 pp 385–392Cite as

DOA Estimation for Nonuniform Linear Arrays Using Root-MUSIC with Sparse Recovery Method

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 212))

Abstract

Direction-of-arrival (DOA) estimation with nonuniform linear arrays (NLA) using the sparse data model is considered. Different with the usually used sparse data model, we introduce a linear interpolation operator which can transform the data of the NLA to the data of a virtual uniform linear array (VULA). We first reduce the dimension of the model using the singular value decomposition technique, next recover the solution of the reduced MMV using a compressed sensing (CS) algorithm, then get the data of the VULA using the recovery result and the linear interpolation operator, and lastly use root-MUSIC to estimating DOA. The method is called CS-RMUSIC. The experiments illustrate the good efficiency of the CS-RMUSIC algorithm.

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Acknowledgements

The work was supported in part by the National Natural Science Foundation of China under grants 61271014, 61072118 and 11101430.

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Authors and Affiliations

  1. Department of Mathematics and System Science, College of Science, National University of Defense Technology, Changsha, 410073, Hunan, People’s Republic of China

    Xinpeng Du, Xiang Xu & Lizhi Cheng

Authors
  1. Xinpeng Du
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  2. Xiang Xu
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  3. Lizhi Cheng
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Corresponding author

Correspondence to Xinpeng Du .

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Editors and Affiliations

  1. School of Science, Anhui University of Science & Technology, Huainan, China

    Zhixiang Yin

  2. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  3. Anhui University of Science & Technology, Huainan, China

    Xianwen Fang

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© 2013 Springer-Verlag Berlin Heidelberg

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Du, X., Xu, X., Cheng, L. (2013). DOA Estimation for Nonuniform Linear Arrays Using Root-MUSIC with Sparse Recovery Method. In: Yin, Z., Pan, L., Fang, X. (eds) Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013. Advances in Intelligent Systems and Computing, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37502-6_47

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  • DOI: https://doi.org/10.1007/978-3-642-37502-6_47

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37501-9

  • Online ISBN: 978-3-642-37502-6

  • eBook Packages: EngineeringEngineering (R0)

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