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


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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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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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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  • DOA estimation
  • Compressed sensing
  • RIPless theory