Print Email Facebook Twitter Integrated Sensing and Communication in UAV Swarms for Cooperative Multiple Targets Tracking Title Integrated Sensing and Communication in UAV Swarms for Cooperative Multiple Targets Tracking Author Zhou, Longyu (University of Electronic Science and Technology of China (UESTC)) Leng, Supeng (University of Electronic Science and Technology of China (UESTC)) Wang, Q. (TU Delft Embedded Systems) Liu, Qiang (University of Electronic Science and Technology of China (UESTC)) Date 2023 Abstract Various interconnected Internet of Things (IoT) devices have emerged, led by the intelligence of the IoT, to realize exceptional interaction with the physical world. In this context, UAV swarm-enabled Multiple Targets Tracking (UAV-MTT), which can sense and track mobile targets for many applications such as hit-and-run, is an appealing topic. Unfortunately, UAVs cannot implement real-time MTT based on the traditional centralized pattern due to the complicated road network environment. It is also challenging to realize low-overhead UAV swarm cooperation in a distributed architecture for the real-time MTT. To address the problem, we propose a cyber-twin-based distributed tracking algorithm to update and optimize a trained digital model for real-time MTT. We then design a distributed cooperative tracking framework to promote MTT performance. In the design, both short-distance and long-distance distributed tracking cooperation manners are first realized with low energy consumption in communication by integrating resources of sensing and communication. Resource integration promotes target sensing efficiency with a highly successful tracking ratio as well. Theoretical derivation proves our algorithmic convergence. Hardware-in-the-loop simulation results demonstrate that our proposed algorithm can remarkably save 65.7% energy consumption in communication compared to other benchmarks while efficiently promoting 20.0% sensing performance. Subject Integrated sensing and communicationUAV swarmTarget trackingcyber-twin To reference this document use: http://resolver.tudelft.nl/uuid:41d54d45-250a-4cfb-b5b5-4b129994adb2 DOI https://doi.org/10.1109/TMC.2022.3193499 Embargo date 2023-10-05 ISSN 1536-1233 Source IEEE Transactions on Mobile Computing, 22 (11), 6526-6542 Part of collection Institutional Repository Document type journal article Rights © 2023 Longyu Zhou, Supeng Leng, Q. Wang, Qiang Liu Files PDF Integrated_Sensing_and_Co ... acking.pdf 2.75 MB Close viewer /islandora/object/uuid:41d54d45-250a-4cfb-b5b5-4b129994adb2/datastream/OBJ/view