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
Cet article présente une technique de suppression des interférences et de restauration du signal qui peut créer les signaux propres requis par les systèmes radar à ondes continues modulés en fréquence pour automobiles. Lorsqu'un signal radar provenant d'un autre système radar interfère avec le propre signal radar émis, les performances de détection de cible sont dégradées. En effet, la fréquence de battement correspondant à la cible ne peut être estimée en raison de l'augmentation du bruit de fond. Dans ce cas, une normalisation avancée de l'enveloppe pondérée ou un débruitage par ondelettes peuvent être utilisés pour atténuer l'effet de l'interférence ; cependant, ces méthodes peuvent également conduire à la perte du signal souhaité contenant les informations de portée et de vitesse de la cible. Par conséquent, nous proposons une méthode basée sur un modèle autorégressif pour restaurer un signal endommagé par une interférence mutuelle. La méthode utilise des signaux qui ne sont pas influencés par les interférences pour restaurer le signal. Dans des expériences menées avec deux systèmes radar automobiles différents, il a été démontré que la méthode proposée supprime efficacement les interférences et rétablit le signal souhaité. En conséquence, le bruit de fond résultant de l’interférence mutuelle a été réduit et la fréquence de battement correspondant à la cible souhaitée a été estimée avec précision.
Sohee LIM
Seoul National University
Seongwook LEE
Samsung Advanced Institute of Technology (SAIT)
Jung-Hwan CHOI
Mando Corporation
Jungmin YOON
Seoul National University
Seong-Cheol KIM
Seoul National University
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Sohee LIM, Seongwook LEE, Jung-Hwan CHOI, Jungmin YOON, Seong-Cheol KIM, "Mutual Interference Suppression and Signal Restoration in Automotive FMCW Radar Systems" in IEICE TRANSACTIONS on Communications,
vol. E102-B, no. 6, pp. 1198-1208, June 2019, doi: 10.1587/transcom.2018EBP3175.
Abstract: This paper presents an interference suppression and signal restoration technique that can create the clean signals required by automotive frequency-modulated continuous wave radar systems. When a radar signal from another radar system interferes with own transmitted radar signal, the target detection performance is degraded. This is because the beat frequency corresponding to the target cannot be estimated owing to the increase in the noise floor. In this case, advanced weighted-envelope normalization or wavelet denoising can be used to mitigate the effect of the interference; however, these methods can also lead to the loss of the desired signal containing the range and velocity information of the target. Therefore, we propose a method based on an autoregressive model to restore a signal damaged by mutual interference. The method uses signals that are not influenced by the interference to restore the signal. In experiments conducted using two different automotive radar systems, our proposed method is demonstrated to effectively suppress the interference and restore the desired signal. As a result, the noise floor resulting from the mutual interference was lowered and the beat frequency corresponding to the desired target was accurately estimated.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2018EBP3175/_p
Copier
@ARTICLE{e102-b_6_1198,
author={Sohee LIM, Seongwook LEE, Jung-Hwan CHOI, Jungmin YOON, Seong-Cheol KIM, },
journal={IEICE TRANSACTIONS on Communications},
title={Mutual Interference Suppression and Signal Restoration in Automotive FMCW Radar Systems},
year={2019},
volume={E102-B},
number={6},
pages={1198-1208},
abstract={This paper presents an interference suppression and signal restoration technique that can create the clean signals required by automotive frequency-modulated continuous wave radar systems. When a radar signal from another radar system interferes with own transmitted radar signal, the target detection performance is degraded. This is because the beat frequency corresponding to the target cannot be estimated owing to the increase in the noise floor. In this case, advanced weighted-envelope normalization or wavelet denoising can be used to mitigate the effect of the interference; however, these methods can also lead to the loss of the desired signal containing the range and velocity information of the target. Therefore, we propose a method based on an autoregressive model to restore a signal damaged by mutual interference. The method uses signals that are not influenced by the interference to restore the signal. In experiments conducted using two different automotive radar systems, our proposed method is demonstrated to effectively suppress the interference and restore the desired signal. As a result, the noise floor resulting from the mutual interference was lowered and the beat frequency corresponding to the desired target was accurately estimated.},
keywords={},
doi={10.1587/transcom.2018EBP3175},
ISSN={1745-1345},
month={June},}
Copier
TY - JOUR
TI - Mutual Interference Suppression and Signal Restoration in Automotive FMCW Radar Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 1198
EP - 1208
AU - Sohee LIM
AU - Seongwook LEE
AU - Jung-Hwan CHOI
AU - Jungmin YOON
AU - Seong-Cheol KIM
PY - 2019
DO - 10.1587/transcom.2018EBP3175
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2019
AB - This paper presents an interference suppression and signal restoration technique that can create the clean signals required by automotive frequency-modulated continuous wave radar systems. When a radar signal from another radar system interferes with own transmitted radar signal, the target detection performance is degraded. This is because the beat frequency corresponding to the target cannot be estimated owing to the increase in the noise floor. In this case, advanced weighted-envelope normalization or wavelet denoising can be used to mitigate the effect of the interference; however, these methods can also lead to the loss of the desired signal containing the range and velocity information of the target. Therefore, we propose a method based on an autoregressive model to restore a signal damaged by mutual interference. The method uses signals that are not influenced by the interference to restore the signal. In experiments conducted using two different automotive radar systems, our proposed method is demonstrated to effectively suppress the interference and restore the desired signal. As a result, the noise floor resulting from the mutual interference was lowered and the beat frequency corresponding to the desired target was accurately estimated.
ER -