Name
Title | ||
|---|---|---|
Two-dimensional DOA estimation method of acoustic vector sensor array based on sparse recovery |
Abstract | ||
|---|---|---|
In order to solve the Direction of Arrival (DOA) estimation of fast-moving targets in a strong noisy environment, an auto-paired two-dimensional (2D) DOA estimation algorithm architecture based on the sparse recovery of acoustic vector sensor arrays is proposed. The structure of the array signal autocorrelation operator is similar to the 2D compressed sampling model. Based on the structure of the autocorrelation operator, a 2D DOA estimation sparse recovery model for the Uniform Line Array (ULA) of the acoustic vector sensors is proposed. Meanwhile, the modified Compressive Sampling Matching Pursuit (CoSaMP) algorithm is used to realize the auto-paired 2D DOA estimation. The simulation results show that the method proposed in this paper can effectively suppress noise, and can be used to realize 2D DOA estimation of acoustic vector sensor ULA under a low Signal-to-Noise Ratio (SNR) and small snapshots. (C) 2021 Elsevier Inc. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.dsp.2021.103294 | DIGITAL SIGNAL PROCESSING |
Keywords | DocType | Volume |
Two-dimensional direction of arrival (2D DOA), Acoustic vector sensor, Sparse recovery, Compressive sampling matching pursuit | Journal | 120 |
ISSN | Citations | PageRank |
1051-2004 | 1 | 0.35 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Longkai Liang | 1 | 1 | 0.35 |
| Yiran Shi | 2 | 1 | 0.35 |
| Yaowu Shi | 3 | 1 | 0.35 |
| Zhejia Bai | 4 | 1 | 0.35 |
| Wenchao He | 5 | 1 | 0.35 |