IEICE TRANSACTIONS on Communications
Underdetermined Direction of Arrival Estimation Based on Signal Sparsity
Summary :
An underdetermined direction of arrival estimation method based on signal sparsity is proposed when independent and coherent signals coexist. Firstly, the estimate of the mixing matrix of the impinging signals is obtained by clustering the single source points which are detected by the ratio of time-frequency transforms of the received signals. Then, each column vector of the mixing matrix is processed by exploiting the forward and backward vectors in turn to obtain the directions of arrival of all signals. The number of independent signals and coherent signal groups that can be estimated by the proposed method can be greater than the number of sensors. The validity of the method is demonstrated by simulations.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E102-B No.10 pp.2066-2072
- Publication Date
- 2019/10/01
- Publicized
- 2019/04/12
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2018EBP3365
- Type of Manuscript
- PAPER
- Category
- Antennas and Propagation
Authors
Peng LI
Southeast University
Zhongyuan ZHOU
Southeast University
Mingjie SHENG
Southeast University
Peng HU
Southeast University
Qi ZHOU
Southeast University
Keyword
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Peng LI, Zhongyuan ZHOU, Mingjie SHENG, Peng HU, Qi ZHOU, "Underdetermined Direction of Arrival Estimation Based on Signal Sparsity" in IEICE TRANSACTIONS on Communications,
vol. E102-B, no. 10, pp. 2066-2072, October 2019, doi: 10.1587/transcom.2018EBP3365.
Abstract: An underdetermined direction of arrival estimation method based on signal sparsity is proposed when independent and coherent signals coexist. Firstly, the estimate of the mixing matrix of the impinging signals is obtained by clustering the single source points which are detected by the ratio of time-frequency transforms of the received signals. Then, each column vector of the mixing matrix is processed by exploiting the forward and backward vectors in turn to obtain the directions of arrival of all signals. The number of independent signals and coherent signal groups that can be estimated by the proposed method can be greater than the number of sensors. The validity of the method is demonstrated by simulations.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2018EBP3365/_p
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@ARTICLE{e102-b_10_2066,
author={Peng LI, Zhongyuan ZHOU, Mingjie SHENG, Peng HU, Qi ZHOU, },
journal={IEICE TRANSACTIONS on Communications},
title={Underdetermined Direction of Arrival Estimation Based on Signal Sparsity},
year={2019},
volume={E102-B},
number={10},
pages={2066-2072},
abstract={An underdetermined direction of arrival estimation method based on signal sparsity is proposed when independent and coherent signals coexist. Firstly, the estimate of the mixing matrix of the impinging signals is obtained by clustering the single source points which are detected by the ratio of time-frequency transforms of the received signals. Then, each column vector of the mixing matrix is processed by exploiting the forward and backward vectors in turn to obtain the directions of arrival of all signals. The number of independent signals and coherent signal groups that can be estimated by the proposed method can be greater than the number of sensors. The validity of the method is demonstrated by simulations.},
keywords={},
doi={10.1587/transcom.2018EBP3365},
ISSN={1745-1345},
month={October},}
Copy
TY - JOUR
TI - Underdetermined Direction of Arrival Estimation Based on Signal Sparsity
T2 - IEICE TRANSACTIONS on Communications
SP - 2066
EP - 2072
AU - Peng LI
AU - Zhongyuan ZHOU
AU - Mingjie SHENG
AU - Peng HU
AU - Qi ZHOU
PY - 2019
DO - 10.1587/transcom.2018EBP3365
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2019
AB - An underdetermined direction of arrival estimation method based on signal sparsity is proposed when independent and coherent signals coexist. Firstly, the estimate of the mixing matrix of the impinging signals is obtained by clustering the single source points which are detected by the ratio of time-frequency transforms of the received signals. Then, each column vector of the mixing matrix is processed by exploiting the forward and backward vectors in turn to obtain the directions of arrival of all signals. The number of independent signals and coherent signal groups that can be estimated by the proposed method can be greater than the number of sensors. The validity of the method is demonstrated by simulations.
ER -
English
