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作 者:Pengyue Guo Tianyun Shi Zhen Ma Jing Wang
机构地区:[1]Institute of Electronic Computing Technology,China Academy of Railway Sciences Corporation Limited,Beijing,China [2]School of Information and Electronics,Beijing Institute of Technology,Beijing,China
出 处:《Railway Sciences》2024年第1期97-110,共14页铁道科学(英文)
基 金:supported by the National Natural Science Foundation of China[U2268217].
摘 要:Purpose – The paper aims to solve the problem of personnel intrusion identification within the limits of highspeed railways. It adopts the fusion method of millimeter wave radar and camera to improve the accuracy ofobject recognition in dark and harsh weather conditions.Design/methodology/approach – This paper adopts the fusion strategy of radar and camera linkage toachieve focus amplification of long-distance targets and solves the problem of low illumination by laser lightfilling of the focus point. In order to improve the recognition effect, this paper adopts the YOLOv8 algorithm formulti-scale target recognition. In addition, for the image distortion caused by bad weather, this paper proposesa linkage and tracking fusion strategy to output the correct alarm results.Findings – Simulated intrusion tests show that the proposed method can effectively detect human intrusionwithin 0–200 m during the day and night in sunny weather and can achieve more than 80% recognitionaccuracy for extreme severe weather conditions.Originality/value – (1) The authors propose a personnel intrusion monitoring scheme based on the fusion ofmillimeter wave radar and camera, achieving all-weather intrusion monitoring;(2) The authors propose a newmulti-level fusion algorithm based on linkage and tracking to achieve intrusion target monitoring underadverse weather conditions;(3) The authors have conducted a large number of innovative simulationexperiments to verify the effectiveness of the method proposed in this article.
关 键 词:High-speed rail perimeter Personnel invasion Object detection ALL-WEATHER Radar-camera fusion
分 类 号:U238[交通运输工程—道路与铁道工程]
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