TY - JOUR
T1 - Cooperatively Localizing Multi-Target by Dynamic UAV Formation Equipped with Bearing-only Sensors
AU - Zheng, Juhong
AU - Liu, Dawei
AU - Shen, Hao
AU - Zhao, Guangyu
AU - Ning, Xin
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - In recent years, the applications of UAV swarm equipped with electro-optical pods have become increasingly widespread. Electro-optical pods are passive sensors that can only measure bearing, but not distance. In practical scenarios of UAV swarm continuous tracking of multiple targets, the time-sensitive moving targets may move out of or suddenly into the field of view of UAV. Collaboratively localizing multiple time-sensitive targets based on bearing-only measurements is a significant challenge for UAV swarm. Traditional direction-finding cross location methods have significant errors under noisy conditions. Existing target location algorithms based on filtering require fixed UAV formation to track specific target, making them unsuitable for dynamic formations. In this paper, we model the target motion with a constant velocity and linearize the process of UAV swarm observing the positions of targets. Then we use the Extended Kalman Filter to estimate the position of targets based on the above target motion model and linearized observation model. The observation model allows for changes of the UAV formation tracking a specific target. Emulation experiments in the VICON environment and simulation experiments in the AirSim environment validate the applicability and accuracy of this method in scenarios of dynamic UAV formation cooperatively localizing multiple targets.
AB - In recent years, the applications of UAV swarm equipped with electro-optical pods have become increasingly widespread. Electro-optical pods are passive sensors that can only measure bearing, but not distance. In practical scenarios of UAV swarm continuous tracking of multiple targets, the time-sensitive moving targets may move out of or suddenly into the field of view of UAV. Collaboratively localizing multiple time-sensitive targets based on bearing-only measurements is a significant challenge for UAV swarm. Traditional direction-finding cross location methods have significant errors under noisy conditions. Existing target location algorithms based on filtering require fixed UAV formation to track specific target, making them unsuitable for dynamic formations. In this paper, we model the target motion with a constant velocity and linearize the process of UAV swarm observing the positions of targets. Then we use the Extended Kalman Filter to estimate the position of targets based on the above target motion model and linearized observation model. The observation model allows for changes of the UAV formation tracking a specific target. Emulation experiments in the VICON environment and simulation experiments in the AirSim environment validate the applicability and accuracy of this method in scenarios of dynamic UAV formation cooperatively localizing multiple targets.
KW - collaboration
KW - electro-optical sensor
KW - target localization
KW - UAV swarm
UR - http://www.scopus.com/inward/record.url?scp=105005828220&partnerID=8YFLogxK
U2 - 10.1109/ITOEC63606.2025.10967742
DO - 10.1109/ITOEC63606.2025.10967742
M3 - 会议文章
AN - SCOPUS:105005828220
SN - 2693-308X
SP - 780
EP - 787
JO - IEEE Information Technology and Mechatronics Engineering Conference, ITOEC
JF - IEEE Information Technology and Mechatronics Engineering Conference, ITOEC
IS - 2025
T2 - 8th IEEE Information Technology and Mechatronics Engineering Conference, ITOEC 2025
Y2 - 14 March 2025 through 16 March 2025
ER -