Integrated Sensing and Communication in UAV Swarms for Cooperative Multiple Targets Tracking

Longyu Zhou, Supeng Leng, Qing Wang, Qiang Liu

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)
120 Downloads (Pure)

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.

Original languageEnglish
Article number9839387
Pages (from-to)6526-6542
Number of pages17
JournalIEEE Transactions on Mobile Computing
Volume22
Issue number11
DOIs
Publication statusPublished - 2023

Keywords

  • Integrated sensing and communication
  • UAV swarm
  • Target tracking
  • cyber-twin

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