TY - JOUR
T1 - Integrated Sensing and Communication in UAV Swarms for Cooperative Multiple Targets Tracking
AU - Zhou, Longyu
AU - Leng, Supeng
AU - Wang, Qing
AU - Liu, Qiang
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Integrated sensing and communication
KW - UAV swarm
KW - Target tracking
KW - cyber-twin
UR - http://www.scopus.com/inward/record.url?scp=85135749800&partnerID=8YFLogxK
U2 - 10.1109/TMC.2022.3193499
DO - 10.1109/TMC.2022.3193499
M3 - Article
AN - SCOPUS:85135749800
SN - 1536-1233
VL - 22
SP - 6526
EP - 6542
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 11
M1 - 9839387
ER -