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.
Highlights
In recent years, UAVs (Unmanned Aerial Vehicles) are playing an increasingly important role in collaborative investigation, battlefield combat, target status monitoring and other fields [1,2,3]
One of the most popular area is the multi-UAVs cooperative target tracking problem which can be abstracted as a mobile sensor network configuration problem [4,5,6,7,8]
There have been some researches on target tracking problem with communication awareness [9,10,11,12], but the communication models ignore the impact of interference and attenuation
Summary
UAVs (Unmanned Aerial Vehicles) are playing an increasingly important role in collaborative investigation, battlefield combat, target status monitoring and other fields [1,2,3]. UAVs as flying base stations in a device-to-device communication network, SINR model was used in Reference [13] to quantify communication quality. The method proposed in Reference [9] raised a communication probability model calculating the probability of successful information transmission between UAVs according to the signal-to-noise ratio. This probability and information was used to calculate UAV expected information, which could be used as criterion for maneuver decision-making. Information transmission is not just successful or not; there may be interference from the environment or other UAVs. In order to describe the communication in a better way, the concept of “communication noise” was raised in Reference [11]. The results show that the proposed method is superior to the communication probability model in terms of target state estimation
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
