{"title":"面向电子信号检测与定位的无人机群鲁棒拓扑恢复研究","authors":"Linfeng Liu;Wenzhe Zhang;Xingyu Li;Jia Xu","doi":"10.1109/TMC.2025.3586447","DOIUrl":null,"url":null,"abstract":"At present, Unmanned Aerial Vehicle (UAV) swarm has been extensively applied in various fields. In the application of detection and localization of electronic signals, some UAVs could become disabled due to some abnormal events (e.g. electromagnetic interference and battery electricity exhaustion), and the topology connectivity of UAV swarm could be impaired, i.e., the topology of UAV swarm could be partitioned. For the topology recovery issue, we first propose Robust Topology Recovery Algorithm of UAV swarm (RTRA) to recover the topology connectivity of UAV swarm and enhance the topology robustness (reduce the number of potential topology recoveries in future) by relocating some UAVs to new positions with shortest flight distance. Furthermore, we note that the relocated UAVs are easy to exhaust the battery electricity and fail due to the extra flight movements for the topology recoveries, which affects the topology robustness. To this end, we present Cascading Robust Recovery Topology Algorithm of UAV swarm (CRTRA), which adopts a cascading movement strategy to share the flight movements among multiply relocated UAVs, thus avoiding the battery electricity exhaustion of the relocated UAVs. Extensive simulations and comparisons demonstrate that our proposed CRTRA can effectively recover the topology connectivity of UAV swarm while enhancing the topology robustness and shortening the flight distance of relocated UAVs, and CRTRA is especially suitable for some missions such as the detection and localization of electronic signals where UAVs are prone to fail.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 11","pages":"12595-12610"},"PeriodicalIF":9.2000,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the Robust Topology Recovery of UAV Swarm for Detection and Localization of Electronic Signals\",\"authors\":\"Linfeng Liu;Wenzhe Zhang;Xingyu Li;Jia Xu\",\"doi\":\"10.1109/TMC.2025.3586447\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At present, Unmanned Aerial Vehicle (UAV) swarm has been extensively applied in various fields. In the application of detection and localization of electronic signals, some UAVs could become disabled due to some abnormal events (e.g. electromagnetic interference and battery electricity exhaustion), and the topology connectivity of UAV swarm could be impaired, i.e., the topology of UAV swarm could be partitioned. For the topology recovery issue, we first propose Robust Topology Recovery Algorithm of UAV swarm (RTRA) to recover the topology connectivity of UAV swarm and enhance the topology robustness (reduce the number of potential topology recoveries in future) by relocating some UAVs to new positions with shortest flight distance. Furthermore, we note that the relocated UAVs are easy to exhaust the battery electricity and fail due to the extra flight movements for the topology recoveries, which affects the topology robustness. To this end, we present Cascading Robust Recovery Topology Algorithm of UAV swarm (CRTRA), which adopts a cascading movement strategy to share the flight movements among multiply relocated UAVs, thus avoiding the battery electricity exhaustion of the relocated UAVs. 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引用次数: 0
摘要
目前,无人机群已广泛应用于各个领域。在电子信号的检测与定位应用中,一些无人机可能会因为某些异常事件(如电磁干扰、电池电量耗尽)而导致无人机失能,破坏无人机群的拓扑连通性,即对无人机群的拓扑进行分区。针对拓扑恢复问题,首先提出了无人机群鲁棒拓扑恢复算法(Robust topology recovery Algorithm of UAV swarm, RTRA),通过将部分无人机重新定位到飞行距离最短的新位置,恢复无人机群的拓扑连通性,增强拓扑鲁棒性(减少未来可能的拓扑恢复次数)。此外,我们注意到重新定位的无人机容易耗尽电池电量,并且由于拓扑恢复的额外飞行运动而失效,这影响了拓扑的鲁棒性。为此,提出了无人机群的级联鲁棒恢复拓扑算法(CRTRA),该算法采用级联运动策略,在多个重新定位的无人机之间共享飞行运动,从而避免了重新定位无人机的电池电量耗尽。大量的仿真和比较表明,该算法可以有效地恢复无人机群的拓扑连通性,同时增强了拓扑鲁棒性,缩短了重新定位无人机的飞行距离,特别适用于无人机容易失效的电子信号检测和定位等任务。
On the Robust Topology Recovery of UAV Swarm for Detection and Localization of Electronic Signals
At present, Unmanned Aerial Vehicle (UAV) swarm has been extensively applied in various fields. In the application of detection and localization of electronic signals, some UAVs could become disabled due to some abnormal events (e.g. electromagnetic interference and battery electricity exhaustion), and the topology connectivity of UAV swarm could be impaired, i.e., the topology of UAV swarm could be partitioned. For the topology recovery issue, we first propose Robust Topology Recovery Algorithm of UAV swarm (RTRA) to recover the topology connectivity of UAV swarm and enhance the topology robustness (reduce the number of potential topology recoveries in future) by relocating some UAVs to new positions with shortest flight distance. Furthermore, we note that the relocated UAVs are easy to exhaust the battery electricity and fail due to the extra flight movements for the topology recoveries, which affects the topology robustness. To this end, we present Cascading Robust Recovery Topology Algorithm of UAV swarm (CRTRA), which adopts a cascading movement strategy to share the flight movements among multiply relocated UAVs, thus avoiding the battery electricity exhaustion of the relocated UAVs. Extensive simulations and comparisons demonstrate that our proposed CRTRA can effectively recover the topology connectivity of UAV swarm while enhancing the topology robustness and shortening the flight distance of relocated UAVs, and CRTRA is especially suitable for some missions such as the detection and localization of electronic signals where UAVs are prone to fail.
期刊介绍:
IEEE Transactions on Mobile Computing addresses key technical issues related to various aspects of mobile computing. This includes (a) architectures, (b) support services, (c) algorithm/protocol design and analysis, (d) mobile environments, (e) mobile communication systems, (f) applications, and (g) emerging technologies. Topics of interest span a wide range, covering aspects like mobile networks and hosts, mobility management, multimedia, operating system support, power management, online and mobile environments, security, scalability, reliability, and emerging technologies such as wearable computers, body area networks, and wireless sensor networks. The journal serves as a comprehensive platform for advancements in mobile computing research.