A Computationally Efficient Algorithm for DOA Estimation with Unfolded Coprime Linear Array
In this paper, we investigate the direction of arrival (DOA) estimation problem with unfolded coprime linear array (UCLA) and propose a low computational complexity signal-subspace fitting (SF) algorithm. SF algorithm is able to achieve excellent DOA estimation performance while it requires global a...
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| Published in | Mathematical problems in engineering Vol. 2022; pp. 1 - 12 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Hindawi
05.09.2022
John Wiley & Sons, Inc |
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| Online Access | Get full text |
| ISSN | 1024-123X 1026-7077 1563-5147 1563-5147 |
| DOI | 10.1155/2022/5429488 |
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| Abstract | In this paper, we investigate the direction of arrival (DOA) estimation problem with unfolded coprime linear array (UCLA) and propose a low computational complexity signal-subspace fitting (SF) algorithm. SF algorithm is able to achieve excellent DOA estimation performance while it requires global angular search (GAS). Especially in the several source signals situation, expensive complexity cost causes. To decrease computational complexity, we propose an initialized based SF (ISF) algorithm, which involves the several one dimensional (1D) partial angular search (PAS) instead of the multidimensional GAS. Consequently, the complexity is significantly decreased. Due to the full utilization of the array aperture, the proposed method in UCLA can attain better performance than general CLA (GCLA). In addition, as the SF is attractive in practical application, the proposed ISF algorithm lowers the computational cost, while achieving almost approximate estimation performance as traditional SF and noise subspace fitting (NF). Moreover, numerical simulations are provided and verify the effectiveness and the superiority of the proposed algorithm for the UCLA. |
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| AbstractList | In this paper, we investigate the direction of arrival (DOA) estimation problem with unfolded coprime linear array (UCLA) and propose a low computational complexity signal-subspace fitting (SF) algorithm. SF algorithm is able to achieve excellent DOA estimation performance while it requires global angular search (GAS). Especially in the several source signals situation, expensive complexity cost causes. To decrease computational complexity, we propose an initialized based SF (ISF) algorithm, which involves the several one dimensional (1D) partial angular search (PAS) instead of the multidimensional GAS. Consequently, the complexity is significantly decreased. Due to the full utilization of the array aperture, the proposed method in UCLA can attain better performance than general CLA (GCLA). In addition, as the SF is attractive in practical application, the proposed ISF algorithm lowers the computational cost, while achieving almost approximate estimation performance as traditional SF and noise subspace fitting (NF). Moreover, numerical simulations are provided and verify the effectiveness and the superiority of the proposed algorithm for the UCLA. |
| Author | Pan, Gong Huafei, Yin |
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| Cites_doi | 10.1007/s00034-021-01887-3 10.1049/el.2010.3279 10.1109/29.60109 10.1109/29.32276 10.1109/lcomm.2017.2787698 10.1109/tap.2007.910493 10.3390/s18010253 10.1016/0165-1684(94)00122-g 10.1109/TVT.2017.2732168 10.1049/el:20051577 10.1109/TAES.2009.4805279 10.1109/lcomm.2013.012313.122113 10.1109/LCOMM.2021.3053114 10.3390/s130404272 10.1109/lcomm.2010.102610.101581 10.1049/el.2015.2261 10.1109/78.97999 10.1109/TAES.2013.6621816 10.1109/EUSIPCO.2015.7362901 10.1016/j.sigpro.2012.06.010 10.1080/00207217.2016.1253789 10.1109/twc.2016.2594173 10.1109/ACCESS.2018.2835563 10.1109/lsp.2004.842276 10.1109/TVT.2019.2957511 10.1109/tap.1986.1143830 10.1016/0165-1684(90)90165-u 10.1109/29.17564 10.1049/el.2010.1195 10.1109/rbme.2017.2697950 |
| ContentType | Journal Article |
| Copyright | Copyright © 2022 Gong Pan and Yin Huafei. Copyright © 2022 Gong Pan and Yin Huafei. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 |
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| SubjectTerms | Algorithms Complexity Computational efficiency Computing costs Direction of arrival Eigenvalues Linear arrays Mathematical problems Sensors Signal processing Simulation |
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| Title | A Computationally Efficient Algorithm for DOA Estimation with Unfolded Coprime Linear Array |
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