The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans cette lettre, tout d'abord, un nouveau formateur de faisceau adaptatif utilisant l'algorithme d'analyse des composants indépendants (ICA) est proposé. Grâce à cet algorithme, l'ambiguïté d'amplitude et de phase résultant de la séparation aveugle des sources est supprimée en utilisant la structure spéciale de la matrice des collecteurs de réseau. Cependant, il peut y avoir d'importantes erreurs d'étalonnage lorsque la puissance des interférences est bien supérieure à celle du signal souhaité dans de nombreuses applications telles que le sonar, la radioastronomie, l'ingénierie biomédicale et la détection des tremblements de terre. En conséquence, cela entraînera une réduction significative des performances de séparation. Ensuite, une nouvelle méthode basée sur la combinaison de l'ICA et de l'analyse en composantes primaires (ACP) est proposée pour récupérer l'amplitude du signal souhaité sous forte interférence. Enfin, une simulation informatique est réalisée pour indiquer l’efficacité de nos méthodes. Les résultats de la simulation montrent que les méthodes proposées peuvent obtenir un SNR plus élevé et une estimation de puissance plus précise du signal souhaité que la méthode d'inversion de matrice d'échantillon à chargement diagonal (LSMI) et d'optimisation des performances dans le pire des cas (WCPO).
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},}
Copier
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 -