IEICE TRANSACTIONS on Communications
2-D DOA Estimation of Multiple Signals Based on Sparse L-Shaped Array
Summary :
This paper proposes a novel method for two-dimensional (2-D) direction-of-arrival (DOA) estimation of multiple signals employing a sparse L-shaped array structured by a sparse linear array (SLA), a sparse uniform linear array (SULA) and an auxiliary sensor. In this method, the elevation angles are estimated by using the SLA and an efficient search approach, while the azimuth angle estimation is performed in two stages. In the first stage, the rough azimuth angle estimates are obtained by utilizing a noise-free cross-covariance matrix (CCM), the estimated elevation angles and data from three sensors including the auxiliary sensor. In the second stage, the fine azimuth angle estimates can be achieved by using the shift-invariance property of the SULA and the rough azimuth angle estimates. Without extra pair-matching process, the proposed method can achieve automatic pairing of the 2-D DOA estimates. Simulation results show that our approach outperforms the compared methods, especially in the cases of low SNR, snapshot deficiency and multiple sources.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E101-B No.2 pp.383-391
- Publication Date
- 2018/02/01
- Publicized
- 2017/08/22
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2017ISP0002
- Type of Manuscript
- Special Section PAPER (Special Section on Recent Progress in Antennas and Propagation in Conjunction with Main Topics of ISAP2016)
- Category
- DOA Estimation
Authors
Zhi ZHENG
University of Electronic Science and Technology of China
Yuxuan YANG
University of Electronic Science and Technology of China
Wen-Qin WANG
University of Electronic Science and Technology of China
Guangjun LI
University of Electronic Science and Technology of China
Jiao YANG
University of Electronic Science and Technology of China
Yan GE
University of Electronic Science and Technology of China
Keyword
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Zhi ZHENG, Yuxuan YANG, Wen-Qin WANG, Guangjun LI, Jiao YANG, Yan GE, "2-D DOA Estimation of Multiple Signals Based on Sparse L-Shaped Array" in IEICE TRANSACTIONS on Communications,
vol. E101-B, no. 2, pp. 383-391, February 2018, doi: 10.1587/transcom.2017ISP0002.
Abstract: This paper proposes a novel method for two-dimensional (2-D) direction-of-arrival (DOA) estimation of multiple signals employing a sparse L-shaped array structured by a sparse linear array (SLA), a sparse uniform linear array (SULA) and an auxiliary sensor. In this method, the elevation angles are estimated by using the SLA and an efficient search approach, while the azimuth angle estimation is performed in two stages. In the first stage, the rough azimuth angle estimates are obtained by utilizing a noise-free cross-covariance matrix (CCM), the estimated elevation angles and data from three sensors including the auxiliary sensor. In the second stage, the fine azimuth angle estimates can be achieved by using the shift-invariance property of the SULA and the rough azimuth angle estimates. Without extra pair-matching process, the proposed method can achieve automatic pairing of the 2-D DOA estimates. Simulation results show that our approach outperforms the compared methods, especially in the cases of low SNR, snapshot deficiency and multiple sources.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2017ISP0002/_p
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@ARTICLE{e101-b_2_383,
author={Zhi ZHENG, Yuxuan YANG, Wen-Qin WANG, Guangjun LI, Jiao YANG, Yan GE, },
journal={IEICE TRANSACTIONS on Communications},
title={2-D DOA Estimation of Multiple Signals Based on Sparse L-Shaped Array},
year={2018},
volume={E101-B},
number={2},
pages={383-391},
abstract={This paper proposes a novel method for two-dimensional (2-D) direction-of-arrival (DOA) estimation of multiple signals employing a sparse L-shaped array structured by a sparse linear array (SLA), a sparse uniform linear array (SULA) and an auxiliary sensor. In this method, the elevation angles are estimated by using the SLA and an efficient search approach, while the azimuth angle estimation is performed in two stages. In the first stage, the rough azimuth angle estimates are obtained by utilizing a noise-free cross-covariance matrix (CCM), the estimated elevation angles and data from three sensors including the auxiliary sensor. In the second stage, the fine azimuth angle estimates can be achieved by using the shift-invariance property of the SULA and the rough azimuth angle estimates. Without extra pair-matching process, the proposed method can achieve automatic pairing of the 2-D DOA estimates. Simulation results show that our approach outperforms the compared methods, especially in the cases of low SNR, snapshot deficiency and multiple sources.},
keywords={},
doi={10.1587/transcom.2017ISP0002},
ISSN={1745-1345},
month={February},}
Copy
TY - JOUR
TI - 2-D DOA Estimation of Multiple Signals Based on Sparse L-Shaped Array
T2 - IEICE TRANSACTIONS on Communications
SP - 383
EP - 391
AU - Zhi ZHENG
AU - Yuxuan YANG
AU - Wen-Qin WANG
AU - Guangjun LI
AU - Jiao YANG
AU - Yan GE
PY - 2018
DO - 10.1587/transcom.2017ISP0002
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E101-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2018
AB - This paper proposes a novel method for two-dimensional (2-D) direction-of-arrival (DOA) estimation of multiple signals employing a sparse L-shaped array structured by a sparse linear array (SLA), a sparse uniform linear array (SULA) and an auxiliary sensor. In this method, the elevation angles are estimated by using the SLA and an efficient search approach, while the azimuth angle estimation is performed in two stages. In the first stage, the rough azimuth angle estimates are obtained by utilizing a noise-free cross-covariance matrix (CCM), the estimated elevation angles and data from three sensors including the auxiliary sensor. In the second stage, the fine azimuth angle estimates can be achieved by using the shift-invariance property of the SULA and the rough azimuth angle estimates. Without extra pair-matching process, the proposed method can achieve automatic pairing of the 2-D DOA estimates. Simulation results show that our approach outperforms the compared methods, especially in the cases of low SNR, snapshot deficiency and multiple sources.
ER -
English
