Enregistré dans:
| Auteurs principaux: | , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2510.10796 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866915548971925504 |
|---|---|
| author | Maydani, R. Wang, Y. Sarrazin, J. Ma, B. |
| author_facet | Maydani, R. Wang, Y. Sarrazin, J. Ma, B. |
| contents | Direction-of-arrival (DoA) estimation with leaky-wave antennas (LWAs) offers a compact and cost-effective alternative to conventional antenna arrays but remains challenging in the presence of coherent sources. To address this issue, we propose a spatially filtered sparse Bayesian learning (SF-SBL) framework. Firstly, the field of view (FoV) is divided into angular sectors according to the frequency beam-scanning property of LWAs, and Bayesian inverse problems are then solved within each sector to improve efficiency and reduce computational cost. Both on-grid SBL and off-grid SBL formulations are developed. Simulation results show that the proposed approach achieves robust and accurate DoA estimation, even with coherent sources. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_10796 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Spatially Filtered Sparse Bayesian Learning for Direction-of-Arrival Estimation with Leaky-Wave Antennas Maydani, R. Wang, Y. Sarrazin, J. Ma, B. Signal Processing Direction-of-arrival (DoA) estimation with leaky-wave antennas (LWAs) offers a compact and cost-effective alternative to conventional antenna arrays but remains challenging in the presence of coherent sources. To address this issue, we propose a spatially filtered sparse Bayesian learning (SF-SBL) framework. Firstly, the field of view (FoV) is divided into angular sectors according to the frequency beam-scanning property of LWAs, and Bayesian inverse problems are then solved within each sector to improve efficiency and reduce computational cost. Both on-grid SBL and off-grid SBL formulations are developed. Simulation results show that the proposed approach achieves robust and accurate DoA estimation, even with coherent sources. |
| title | Spatially Filtered Sparse Bayesian Learning for Direction-of-Arrival Estimation with Leaky-Wave Antennas |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2510.10796 |