In this letter, firstly, a novel adaptive beamformer using independent component analysis (ICA) algorithm is proposed. By this algorithm, the ambiguity of amplitude and phase resulted from blind source separation is removed utilizing the special structure of array manifolds matrix. However, there might exist great calibration error when the powers of interferences are far larger than that of desired signal at many applications such as sonar, radio astronomy, biomedical engineering and earthquake detection. As a result, this will lead to a significant reduction in separation performance. Then, a new method based on the combination of ICA and primary component analysis (PCA) is proposed to recover the desired signal's amplitude under strong interference. Finally, computer simulation is carried out to indicate the effectiveness of our methods. The simulation results show that the proposed methods can obtain higher SNR and more accurate power estimation of desired signal than diagonal loading sample matrix inversion (LSMI) and worst-case performance optimization (WCPO) method.
Zongli RUAN
China University of Petroleum
Hongshu LIAO
University of Electronics Science and Technology of China
Guobing QIAN
Southwest University
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Zongli RUAN, Hongshu LIAO, Guobing QIAN, "A Novel Method for Adaptive Beamforming under the Strong Interference Condition" in IEICE TRANSACTIONS on Fundamentals,
vol. E105-A, no. 2, pp. 109-113, February 2022, doi: 10.1587/transfun.2021EAL2045.
Abstract: In this letter, firstly, a novel adaptive beamformer using independent component analysis (ICA) algorithm is proposed. By this algorithm, the ambiguity of amplitude and phase resulted from blind source separation is removed utilizing the special structure of array manifolds matrix. However, there might exist great calibration error when the powers of interferences are far larger than that of desired signal at many applications such as sonar, radio astronomy, biomedical engineering and earthquake detection. As a result, this will lead to a significant reduction in separation performance. Then, a new method based on the combination of ICA and primary component analysis (PCA) is proposed to recover the desired signal's amplitude under strong interference. Finally, computer simulation is carried out to indicate the effectiveness of our methods. The simulation results show that the proposed methods can obtain higher SNR and more accurate power estimation of desired signal than diagonal loading sample matrix inversion (LSMI) and worst-case performance optimization (WCPO) method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2021EAL2045/_p
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@ARTICLE{e105-a_2_109,
author={Zongli RUAN, Hongshu LIAO, Guobing QIAN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Novel Method for Adaptive Beamforming under the Strong Interference Condition},
year={2022},
volume={E105-A},
number={2},
pages={109-113},
abstract={In this letter, firstly, a novel adaptive beamformer using independent component analysis (ICA) algorithm is proposed. By this algorithm, the ambiguity of amplitude and phase resulted from blind source separation is removed utilizing the special structure of array manifolds matrix. However, there might exist great calibration error when the powers of interferences are far larger than that of desired signal at many applications such as sonar, radio astronomy, biomedical engineering and earthquake detection. As a result, this will lead to a significant reduction in separation performance. Then, a new method based on the combination of ICA and primary component analysis (PCA) is proposed to recover the desired signal's amplitude under strong interference. Finally, computer simulation is carried out to indicate the effectiveness of our methods. The simulation results show that the proposed methods can obtain higher SNR and more accurate power estimation of desired signal than diagonal loading sample matrix inversion (LSMI) and worst-case performance optimization (WCPO) method.},
keywords={},
doi={10.1587/transfun.2021EAL2045},
ISSN={1745-1337},
month={February},}
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TY - JOUR
TI - A Novel Method for Adaptive Beamforming under the Strong Interference Condition
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 109
EP - 113
AU - Zongli RUAN
AU - Hongshu LIAO
AU - Guobing QIAN
PY - 2022
DO - 10.1587/transfun.2021EAL2045
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E105-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2022
AB - In this letter, firstly, a novel adaptive beamformer using independent component analysis (ICA) algorithm is proposed. By this algorithm, the ambiguity of amplitude and phase resulted from blind source separation is removed utilizing the special structure of array manifolds matrix. However, there might exist great calibration error when the powers of interferences are far larger than that of desired signal at many applications such as sonar, radio astronomy, biomedical engineering and earthquake detection. As a result, this will lead to a significant reduction in separation performance. Then, a new method based on the combination of ICA and primary component analysis (PCA) is proposed to recover the desired signal's amplitude under strong interference. Finally, computer simulation is carried out to indicate the effectiveness of our methods. The simulation results show that the proposed methods can obtain higher SNR and more accurate power estimation of desired signal than diagonal loading sample matrix inversion (LSMI) and worst-case performance optimization (WCPO) method.
ER -