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

Tianyi Jia (), Haiyan Wang () and Xiaohong Shen ()
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Tianyi Jia: Northwestern Polytechnical University
Haiyan Wang: Northwestern Polytechnical University
Xiaohong Shen: Northwestern Polytechnical University

Telecommunication Systems: Modelling, Analysis, Design and Management, 2020, vol. 74, issue 4, No 10, 537 pages

Abstract: 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.

Keywords: DOA estimation; Compressed sensing; RIPless theory (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11235-020-00676-8

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