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A study of compressed sensing single-snapshot DOA estimation based on the RIPless theory

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Abstract

We explore the RIPless theory for the analysis of single snapshot DOA estimation with uniform linear array using the compressed sensing technique. Starting with a sparse signal recovery model constructed for single snapshot DOA estimation, we prove the isotropy property and incoherence property are fulfilled for the estimation problem. A vital proposition is obtained using the RIPless theory, which establishes the fundamental relationship of the probability of recovery with the number of targets and sensors.

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Acknowledgements

Funding was provided by National Natural Science Foundation of China (Grant Nos. 61571365, 61671386) and Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University (Grant No. CX201939).

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Authors and Affiliations

  1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, 710072, China

    Tianyi Jia, Haiyan Wang & Xiaohong Shen

  2. School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, 710021, Shaanxi, China

    Haiyan Wang

  3. Key Laboratory of Ocean Acoustics and Sensing, Ministry of Industry and Information Technology, Xi’an, 710072, China

    Tianyi Jia & Xiaohong Shen

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  1. Tianyi Jia
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  2. Haiyan Wang
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  3. Xiaohong Shen
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Correspondence to Tianyi Jia.

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Jia, T., Wang, H. & Shen, X. A study of compressed sensing single-snapshot DOA estimation based on the RIPless theory. Telecommun Syst 74, 531–537 (2020). https://doi.org/10.1007/s11235-020-00676-8

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  • DOI: https://doi.org/10.1007/s11235-020-00676-8

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