Multi-UAVs Communication-Aware Cooperative Target Tracking
Source abstract
Abstract
A kind of communication-aware cooperative target tracking algorithm is proposed, which is based on information consensus under multi-Unmanned Aerial Vehicles (UAVs) communication noise. Each UAV uses the extended Kalman filter to predict target movement and get an estimation of target state. The communication between UAVs is modeled as a signal to noise ratio model. During the information fusion process, communication noise is treated as a kind of observation noise, which makes UAVs reach a compromise between observation and communication. The classical consensus algorithm is used to deal with observed information, and consistency prediction of each UAV’s target state is obtained. Each UAV calculates its control inputs using receding horizon optimization method based on consistency results. The simulation results show that introducing communication noise can make UAVs more focused on maintaining good communication with other UAVs in the process of target tracking, and improve the accuracy of cooperative target tracking.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: UAV Applications and Optimization · Distributed Control Multi-Agent Systems · Video Surveillance and Tracking Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
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