IEICE TRANSACTIONS on Fundamentals
Robust Adaptive Beamforming Based on the Effective Steering Vector Estimation and Covariance Matrix Reconstruction against Sensor Gain-Phase Errors
Summary :
A robust adaptive beamforming algorithm is proposed based on the precise interference-plus-noise covariance matrix reconstruction and steering vector estimation of the desired signal, even existing large gain-phase errors. Firstly, the model of array mismatches is proposed with the first-order Taylor series expansion. Then, an iterative method is designed to jointly estimate calibration coefficients and steering vectors of the desired signal and interferences. Next, the powers of interferences and noise are estimated by solving a quadratic optimization question with the derived closed-form solution. At last, the actual interference-plus-noise covariance matrix can be reconstructed as a weighted sum of the steering vectors and the corresponding powers. Simulation results demonstrate the effectiveness and advancement of the proposed method.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E103-A No.12 pp.1655-1658
- Publication Date
- 2020/12/01
- Publicized
- 2020/06/04
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2020EAL2041
- Type of Manuscript
- LETTER
- Category
- Digital Signal Processing
Authors
Di YAO
Harbin Institute of Technology at Weihai
Xin ZHANG
Harbin Institute of Technology
Bin HU
Harbin Institute of Technology
Xiaochuan WU
Harbin Institute of Technology
Keyword
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Di YAO, Xin ZHANG, Bin HU, Xiaochuan WU, "Robust Adaptive Beamforming Based on the Effective Steering Vector Estimation and Covariance Matrix Reconstruction against Sensor Gain-Phase Errors" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 12, pp. 1655-1658, December 2020, doi: 10.1587/transfun.2020EAL2041.
Abstract: A robust adaptive beamforming algorithm is proposed based on the precise interference-plus-noise covariance matrix reconstruction and steering vector estimation of the desired signal, even existing large gain-phase errors. Firstly, the model of array mismatches is proposed with the first-order Taylor series expansion. Then, an iterative method is designed to jointly estimate calibration coefficients and steering vectors of the desired signal and interferences. Next, the powers of interferences and noise are estimated by solving a quadratic optimization question with the derived closed-form solution. At last, the actual interference-plus-noise covariance matrix can be reconstructed as a weighted sum of the steering vectors and the corresponding powers. Simulation results demonstrate the effectiveness and advancement of the proposed method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2020EAL2041/_p
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@ARTICLE{e103-a_12_1655,
author={Di YAO, Xin ZHANG, Bin HU, Xiaochuan WU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Robust Adaptive Beamforming Based on the Effective Steering Vector Estimation and Covariance Matrix Reconstruction against Sensor Gain-Phase Errors},
year={2020},
volume={E103-A},
number={12},
pages={1655-1658},
abstract={A robust adaptive beamforming algorithm is proposed based on the precise interference-plus-noise covariance matrix reconstruction and steering vector estimation of the desired signal, even existing large gain-phase errors. Firstly, the model of array mismatches is proposed with the first-order Taylor series expansion. Then, an iterative method is designed to jointly estimate calibration coefficients and steering vectors of the desired signal and interferences. Next, the powers of interferences and noise are estimated by solving a quadratic optimization question with the derived closed-form solution. At last, the actual interference-plus-noise covariance matrix can be reconstructed as a weighted sum of the steering vectors and the corresponding powers. Simulation results demonstrate the effectiveness and advancement of the proposed method.},
keywords={},
doi={10.1587/transfun.2020EAL2041},
ISSN={1745-1337},
month={December},}
Copy
TY - JOUR
TI - Robust Adaptive Beamforming Based on the Effective Steering Vector Estimation and Covariance Matrix Reconstruction against Sensor Gain-Phase Errors
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1655
EP - 1658
AU - Di YAO
AU - Xin ZHANG
AU - Bin HU
AU - Xiaochuan WU
PY - 2020
DO - 10.1587/transfun.2020EAL2041
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2020
AB - A robust adaptive beamforming algorithm is proposed based on the precise interference-plus-noise covariance matrix reconstruction and steering vector estimation of the desired signal, even existing large gain-phase errors. Firstly, the model of array mismatches is proposed with the first-order Taylor series expansion. Then, an iterative method is designed to jointly estimate calibration coefficients and steering vectors of the desired signal and interferences. Next, the powers of interferences and noise are estimated by solving a quadratic optimization question with the derived closed-form solution. At last, the actual interference-plus-noise covariance matrix can be reconstructed as a weighted sum of the steering vectors and the corresponding powers. Simulation results demonstrate the effectiveness and advancement of the proposed method.
ER -
English
