IEICE TRANSACTIONS on Communications
Wideband Adaptive Beamforming Algorithm for Conformal Arrays Based on Sparse Covariance Matrix Reconstruction
Summary :
Aiming at solving the performance degradation caused by the covariance matrix mismatch in wideband beamforming for conformal arrays, a novel adaptive beamforming algorithm is proposed in this paper. In this algorithm, the interference-plus-noise covariance matrix is firstly reconstructed to solve the desired signal contamination problem. Then, a sparse reconstruction method is utilized to reduce the high computational cost and the requirement of sampling data. A novel cost function is formulated by the focusing matrix and singular value decomposition. Finally, the optimization problem is efficiently solved in a second-order cone programming framework. Simulation results using a cylindrical array demonstrate the effectiveness and robustness of the proposed algorithm and prove that this algorithm can achieve superior performance over the existing wideband beamforming methods for conformal arrays.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E101-B No.2 pp.548-554
- Publication Date
- 2018/02/01
- Publicized
- 2017/08/22
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2016EBP3495
- Type of Manuscript
- PAPER
- Category
- Antennas and Propagation
Authors
Pei CHEN
Zhengzhou Institute of Information Science and Technology
Dexiu HU
Zhengzhou Institute of Information Science and Technology
Yongjun ZHAO
Zhengzhou Institute of Information Science and Technology
Chengcheng LIU
Zhengzhou Institute of Information Science and Technology
Keyword
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Pei CHEN, Dexiu HU, Yongjun ZHAO, Chengcheng LIU, "Wideband Adaptive Beamforming Algorithm for Conformal Arrays Based on Sparse Covariance Matrix Reconstruction" in IEICE TRANSACTIONS on Communications,
vol. E101-B, no. 2, pp. 548-554, February 2018, doi: 10.1587/transcom.2016EBP3495.
Abstract: Aiming at solving the performance degradation caused by the covariance matrix mismatch in wideband beamforming for conformal arrays, a novel adaptive beamforming algorithm is proposed in this paper. In this algorithm, the interference-plus-noise covariance matrix is firstly reconstructed to solve the desired signal contamination problem. Then, a sparse reconstruction method is utilized to reduce the high computational cost and the requirement of sampling data. A novel cost function is formulated by the focusing matrix and singular value decomposition. Finally, the optimization problem is efficiently solved in a second-order cone programming framework. Simulation results using a cylindrical array demonstrate the effectiveness and robustness of the proposed algorithm and prove that this algorithm can achieve superior performance over the existing wideband beamforming methods for conformal arrays.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2016EBP3495/_p
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@ARTICLE{e101-b_2_548,
author={Pei CHEN, Dexiu HU, Yongjun ZHAO, Chengcheng LIU, },
journal={IEICE TRANSACTIONS on Communications},
title={Wideband Adaptive Beamforming Algorithm for Conformal Arrays Based on Sparse Covariance Matrix Reconstruction},
year={2018},
volume={E101-B},
number={2},
pages={548-554},
abstract={Aiming at solving the performance degradation caused by the covariance matrix mismatch in wideband beamforming for conformal arrays, a novel adaptive beamforming algorithm is proposed in this paper. In this algorithm, the interference-plus-noise covariance matrix is firstly reconstructed to solve the desired signal contamination problem. Then, a sparse reconstruction method is utilized to reduce the high computational cost and the requirement of sampling data. A novel cost function is formulated by the focusing matrix and singular value decomposition. Finally, the optimization problem is efficiently solved in a second-order cone programming framework. Simulation results using a cylindrical array demonstrate the effectiveness and robustness of the proposed algorithm and prove that this algorithm can achieve superior performance over the existing wideband beamforming methods for conformal arrays.},
keywords={},
doi={10.1587/transcom.2016EBP3495},
ISSN={1745-1345},
month={February},}
Copy
TY - JOUR
TI - Wideband Adaptive Beamforming Algorithm for Conformal Arrays Based on Sparse Covariance Matrix Reconstruction
T2 - IEICE TRANSACTIONS on Communications
SP - 548
EP - 554
AU - Pei CHEN
AU - Dexiu HU
AU - Yongjun ZHAO
AU - Chengcheng LIU
PY - 2018
DO - 10.1587/transcom.2016EBP3495
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E101-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2018
AB - Aiming at solving the performance degradation caused by the covariance matrix mismatch in wideband beamforming for conformal arrays, a novel adaptive beamforming algorithm is proposed in this paper. In this algorithm, the interference-plus-noise covariance matrix is firstly reconstructed to solve the desired signal contamination problem. Then, a sparse reconstruction method is utilized to reduce the high computational cost and the requirement of sampling data. A novel cost function is formulated by the focusing matrix and singular value decomposition. Finally, the optimization problem is efficiently solved in a second-order cone programming framework. Simulation results using a cylindrical array demonstrate the effectiveness and robustness of the proposed algorithm and prove that this algorithm can achieve superior performance over the existing wideband beamforming methods for conformal arrays.
ER -
English
