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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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
- DOA estimation
- Compressed sensing
- RIPless theory