IEICE TRANSACTIONS on Communications
Real-Valued Reweighted l1 Norm Minimization Method Based on Data Reconstruction in MIMO Radar
Summary :
In this paper, a real-valued reweighted l1 norm minimization method based on data reconstruction in monostatic multiple-input multiple-output (MIMO) radar is proposed. Exploiting the special structure of the received data, and through the received data reconstruction approach and unitary transformation technique, a one-dimensional real-valued received data matrix can be obtained for recovering the sparse signal. Then a weight matrix based on real-valued MUSIC spectrum is designed for reweighting l1 norm minimization to enhance the sparsity of solution. Finally, the DOA can be estimated by finding the non-zero rows in the recovered matrix. Compared with traditional l1 norm-based minimization methods, the proposed method provides better angle estimation performance. Simulation results are presented to verify the effectiveness and advantage of the proposed method.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E98-B No.11 pp.2307-2313
- Publication Date
- 2015/11/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E98.B.2307
- Type of Manuscript
- PAPER
- Category
- Antennas and Propagation
Authors
Qi LIU
Harbin Engineering University
Wei WANG
Harbin Engineering University
Dong LIANG
Harbin Engineering University
Xianpeng WANG
Harbin Engineering University
Keyword
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Qi LIU, Wei WANG, Dong LIANG, Xianpeng WANG, "Real-Valued Reweighted l1 Norm Minimization Method Based on Data Reconstruction in MIMO Radar" in IEICE TRANSACTIONS on Communications,
vol. E98-B, no. 11, pp. 2307-2313, November 2015, doi: 10.1587/transcom.E98.B.2307.
Abstract: In this paper, a real-valued reweighted l1 norm minimization method based on data reconstruction in monostatic multiple-input multiple-output (MIMO) radar is proposed. Exploiting the special structure of the received data, and through the received data reconstruction approach and unitary transformation technique, a one-dimensional real-valued received data matrix can be obtained for recovering the sparse signal. Then a weight matrix based on real-valued MUSIC spectrum is designed for reweighting l1 norm minimization to enhance the sparsity of solution. Finally, the DOA can be estimated by finding the non-zero rows in the recovered matrix. Compared with traditional l1 norm-based minimization methods, the proposed method provides better angle estimation performance. Simulation results are presented to verify the effectiveness and advantage of the proposed method.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E98.B.2307/_p
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@ARTICLE{e98-b_11_2307,
author={Qi LIU, Wei WANG, Dong LIANG, Xianpeng WANG, },
journal={IEICE TRANSACTIONS on Communications},
title={Real-Valued Reweighted l1 Norm Minimization Method Based on Data Reconstruction in MIMO Radar},
year={2015},
volume={E98-B},
number={11},
pages={2307-2313},
abstract={In this paper, a real-valued reweighted l1 norm minimization method based on data reconstruction in monostatic multiple-input multiple-output (MIMO) radar is proposed. Exploiting the special structure of the received data, and through the received data reconstruction approach and unitary transformation technique, a one-dimensional real-valued received data matrix can be obtained for recovering the sparse signal. Then a weight matrix based on real-valued MUSIC spectrum is designed for reweighting l1 norm minimization to enhance the sparsity of solution. Finally, the DOA can be estimated by finding the non-zero rows in the recovered matrix. Compared with traditional l1 norm-based minimization methods, the proposed method provides better angle estimation performance. Simulation results are presented to verify the effectiveness and advantage of the proposed method.},
keywords={},
doi={10.1587/transcom.E98.B.2307},
ISSN={1745-1345},
month={November},}
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TY - JOUR
TI - Real-Valued Reweighted l1 Norm Minimization Method Based on Data Reconstruction in MIMO Radar
T2 - IEICE TRANSACTIONS on Communications
SP - 2307
EP - 2313
AU - Qi LIU
AU - Wei WANG
AU - Dong LIANG
AU - Xianpeng WANG
PY - 2015
DO - 10.1587/transcom.E98.B.2307
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E98-B
IS - 11
JA - IEICE TRANSACTIONS on Communications
Y1 - November 2015
AB - In this paper, a real-valued reweighted l1 norm minimization method based on data reconstruction in monostatic multiple-input multiple-output (MIMO) radar is proposed. Exploiting the special structure of the received data, and through the received data reconstruction approach and unitary transformation technique, a one-dimensional real-valued received data matrix can be obtained for recovering the sparse signal. Then a weight matrix based on real-valued MUSIC spectrum is designed for reweighting l1 norm minimization to enhance the sparsity of solution. Finally, the DOA can be estimated by finding the non-zero rows in the recovered matrix. Compared with traditional l1 norm-based minimization methods, the proposed method provides better angle estimation performance. Simulation results are presented to verify the effectiveness and advantage of the proposed method.
ER -
English
