Manifold Ambiguity-Free Low Complexity DOA Estimation Method for Unfolded Co-Prime Arrays
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| Titel: | Manifold Ambiguity-Free Low Complexity DOA Estimation Method for Unfolded Co-Prime Arrays |
|---|---|
| Autoren: | Ashok C, Venkateswaran N |
| Quelle: | IEEE Communications Letters. 25:1886-1890 |
| Verlagsinformationen: | Institute of Electrical and Electronics Engineers (IEEE), 2021. |
| Publikationsjahr: | 2021 |
| Schlagwörter: | 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology |
| Beschreibung: | The problem of manifold ambiguity-free direction-of-arrival (DOA) estimation for an unfolded co-prime array is of prime research interest. The manifold ambiguity problem is resolved by using beamforming-like methods. However, the performance of this method is limited by the searching step, computational complexity and also fails to resolve the closely spaced sources. In order to overcome the above limitations, in this letter, the DOA estimation is viewed as a function approximation problem. The unknown mapping function that relates the received signals and its DOAs is approximated by using the support vector regression (SVR). The proposed method resolves the ambiguity problem completely with low computational complexity. The simulation results are provided to validate the superiority and effectiveness of DOA estimation in terms of estimation accuracy, computational complexity and reliability. |
| Publikationsart: | Article |
| ISSN: | 2373-7891 1089-7798 |
| DOI: | 10.1109/lcomm.2021.3059673 |
| Zugangs-URL: | https://dblp.uni-trier.de/db/journals/icl/icl25.html#CN21 https://ieeexplore.ieee.org/document/9358168 http://ieeexplore.ieee.org/document/9358168 |
| Rights: | IEEE Copyright |
| Dokumentencode: | edsair.doi.dedup.....8dc42c44f7b51e85e6e0feb20d60f2a0 |
| Datenbank: | OpenAIRE |
| Abstract: | The problem of manifold ambiguity-free direction-of-arrival (DOA) estimation for an unfolded co-prime array is of prime research interest. The manifold ambiguity problem is resolved by using beamforming-like methods. However, the performance of this method is limited by the searching step, computational complexity and also fails to resolve the closely spaced sources. In order to overcome the above limitations, in this letter, the DOA estimation is viewed as a function approximation problem. The unknown mapping function that relates the received signals and its DOAs is approximated by using the support vector regression (SVR). The proposed method resolves the ambiguity problem completely with low computational complexity. The simulation results are provided to validate the superiority and effectiveness of DOA estimation in terms of estimation accuracy, computational complexity and reliability. |
|---|---|
| ISSN: | 23737891 10897798 |
| DOI: | 10.1109/lcomm.2021.3059673 |
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