Name
Title | ||
|---|---|---|
Direction-of-Arrival Estimation Through Exact Continuous ℓ<sub>2,0</sub>-Norm Relaxation |
Abstract | ||
|---|---|---|
On-grid based direction-of-arrival (DOA) estimation methods rely on the resolution of a difficult group-sparse optimization problem that involves the ℓ
<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2,0</sub>
pseudo-norm. In this work, we show that an exact relaxation of this problem can be obtained by replacing the ℓ
<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2,0</sub>
term with a group minimax concave penalty with suitable parameters. This relaxation is more amenable to non-convex optimization algorithms as it is continuous and admits less local (not global) minimizers than the initial ℓ
<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2,0</sub>
-regularized criteria. We then show on numerical simulations that the minimization of the proposed relaxation with an iteratively reweighted ℓ
<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2,0</sub>
algorithm leads to an improved performance over traditional approaches. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/LSP.2020.3042771 | IEEE Signal Processing Letters |
Keywords | DocType | Volume |
$\ell _{2,0}$ -norm minimization,DOA,exact relaxations,MMV-sparse optimization | Journal | 28 |
ISSN | Citations | PageRank |
1070-9908 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emmanuel Soubies | 1 | 5 | 7.29 |
| Adilson Chinatto | 2 | 1 | 1.03 |
| Pascal Larzabal | 3 | 535 | 64.76 |
| Joao Marcos T. Romano | 4 | 0 | 0.34 |
| Laure Blanc-Féraud | 5 | 0 | 1.35 |