Name
Abstract | ||
|---|---|---|
Standard sparse algorithms always assume that all the azimuths lie in prior discretized spatial grids in direction-of-arrival (DOA) estimations. However, this assumption may lead to poor performance in practice owing to the spatial arbitrariness of true azimuths. Several techniques have been proposed to overcome this off-the-grid issue, but the performance of these techniques is not satisfactory (i.e., they are either inaccurate or computationally expensive). In this letter, we propose a post-processing algorithm, called dynamic parameterized 1 -regulation, which efficiently provides compressed-sensing-based single-snapshot DOA estimations. The advantages of our proposed algorithm are verified from our numerical results. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LCOMM.2017.2725268 | IEEE Communications Letters |
Keywords | Field | DocType |
Heuristic algorithms,Estimation,Azimuth,Direction-of-arrival estimation,Sensors,Matching pursuit algorithms,Standards | Discretization,Mathematical optimization,Parameterized complexity,Arbitrariness,Computer science,Algorithm,Azimuth,Real-time computing,Snapshot (computer storage),Matching pursuit algorithms | Journal |
Volume | Issue | ISSN |
21 | 10 | 1089-7798 |
Citations | PageRank | References |
1 | 0.38 | 7 |
Authors | ||
2 | ||