Real-Valued Reweighted <I>l</I><SUB>1</SUB> Norm Minimization Method Based on Data Reconstruction in MIMO Radar

Qi LIU; Wei WANG; Dong LIANG; Xianpeng WANG

doi:10.1587/transcom.E98.B.2307

Real-Valued Reweighted l₁ Norm Minimization Method Based on Data Reconstruction in MIMO Radar

Qi LIU, Wei WANG, Dong LIANG, Xianpeng WANG

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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

MIMO radar, DOA estimation, sparse representation, real-valued reweighted l₁ norm minimization

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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://globals.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 -