Qi, Jialin (Beihang University), Zhang, Zheng (Beihang University), Dong, Xiwang (Beihang University), Yu, Jianglong (Beihang University), Li, Qingdong (Beihang University), Jiang, Hong (Beihang University), Ren, Zhang (Beihang University)

Time-Varying Formation Tracking with Distributed Multi-Sensor Multi-Target Filtering

Scheduled for presentation during the Regular Session "Sensor Fusion" (ThA1), Thursday, June 8, 2023, 10:00−10:20, Room 118

2023 International Conference on Unmanned Aircraft Systems (ICUAS), June 6-9, 2023, Lazarski University, Warsaw, Poland

This information is tentative and subject to change. Compiled on April 26, 2024

Abstract

Formation tracking is used widely in targets enclosing, monitoring and striking, however, in practical scenes, the targets are always uncooperative. The problem of time-varying formation tracking for multiagent with multi-target which states are unknown is studied in this paper. In order to obtain the accurate state estimations of targets, a distributed multi-sensor multi-target filtering algorithm based on the cubature Kalman filter scheme and multiple heterogeneous sensors is proposed. Then, the state estimations obtained by the filtering algorithm are used to design a time-varying formation tracking protocol for multiagent, enabling multiagent to form a time-varying formation to track the convex combination of targets. Finally, the effectiveness of this proposed algorithm is illustrated by simulation experiments.