Name
Title | ||
|---|---|---|
Subspace And Sparse Reconstruction Based Near-Field Sources Localization In Uniform Linear Array |
Abstract | ||
|---|---|---|
This work studies the near-field localization problem using a symmetry uniform linear array (ULA). To decouple the range and direction of arrival (DOA), by exploiting the symmetry property of the array, two spatial correlation sequences are constructed, where each sequence only corresponds to one parameter, i.e., DOA or range. After decoupling, an attractive property is that the resulting sequences still share the similar ULA spatial structure. To perform DOA estimation, two approaches have been developed. The first one is based on the power of R (POR) method, which obtains the noise subspace without the eigendecomposition and prior information of the number of sources. The second one is developed using atomic norm minimization, which eliminates the off-grid issue. For range estimation, since the constructed sequence that corresponds to the range parameter shares the same spatial structure with the DOA sequence, the developed approaches are readily applied to obtain the range estimates. The proposed approach is also studied under one-bit measurement to show its robustness. The numerical studies including simulation and real-world data demonstrate the performance of the proposed method. (C) 2020 Elsevier Inc. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.dsp.2020.102824 | DIGITAL SIGNAL PROCESSING |
Keywords | DocType | Volume |
Near-field localization, Power of R, Atomic norm, Uniform linear array | Journal | 106 |
ISSN | Citations | PageRank |
1051-2004 | 1 | 0.35 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongqing Liu | 1 | 45 | 28.77 |
| Huan Meng | 2 | 1 | 0.35 |
| Lu Gan | 3 | 1 | 0.35 |
| Dong Li | 4 | 10 | 2.63 |
| Yi Zhou | 5 | 15 | 9.83 |
| Trieu-Kien Truong | 6 | 382 | 59.00 |