Multi-UAV cooperative target tracking with bounded noise for connectivity preservation
- PDF / 1,088,291 Bytes
- 10 Pages / 595.276 x 841.89 pts (A4) Page_size
- 93 Downloads / 164 Views
1494
2020 21(10):1494-1503
Frontiers of Information Technology & Electronic Engineering www.jzus.zju.edu.cn; engineering.cae.cn; www.springerlink.com ISSN 2095-9184 (print); ISSN 2095-9230 (online) E-mail: [email protected]
Multi-UAV cooperative target tracking with bounded noise for connectivity preservation∗ Rui ZHOU1 , Yu FENG1 , Bin DI2 , Jiang ZHAO†‡1 , Yan HU1,3 1School 2National
of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Innovation Institute of Defense Technology, Academy of Military Sciences PLA China, Beijing 100171, China 3CETC
Key Laboratory of Aerospace Information Applications, Shijiazhuang 050081, China † E-mail:
[email protected]
Received Nov. 12, 2019; Revision accepted Jan. 3, 2020; Crosschecked July 28, 2020
Abstract: We investigate cooperative target tracking of multiple unmanned aerial vehicles (UAVs) with a limited communication range. This is an integration of UAV motion control, target state estimation, and network topology control. We first present the communication topology and basic notations for network connectivity, and introduce the distributed Kalman consensus filter. Then, convergence and boundedness of the estimation errors using the filter are analyzed, and potential functions are proposed for communication link maintenance and collision avoidance. By taking stable target tracking into account, a distributed potential function based UAV motion controller is discussed. Since only the estimation of the target state rather than the state itself is available for UAV motion control and UAV motion can also affect the accuracy of state estimation, it is clear that the UAV motion control and target state estimation are coupled. Finally, the stability and convergence properties of the coupled system under bounded noise are analyzed in detail and demonstrated by simulations. Key words: Multi-UAV cooperative target tracking; Network connectivity; Kalman consensus filter; Bounded noise; Connectivity preservation https://doi.org/10.1631/FITEE.1900617 CLC number: TN953; TP391.41
1 Introduction Cooperative target tracking of multiple unmanned aerial vehicles (UAVs) has received significant attention in recent years. It is believed that multiple UAVs can improve the estimation accuracy and tracking robustness in comparison with a single UAV (Kim et al., 2010; Yan et al., 2017). MultiUAV organization, distributed estimation and information fusion methods, and UAV motion control ‡ *
Corresponding author
Project supported by the National Natural Science Foundation of China (Nos. 61773031, 61573042, 61803009, and 61903084) and the Jiangsu Province Science Foundation for Youths, China (No. BK20180358) ORCID: Rui ZHOU, https://orcid.org/0000-0003-2476-1130; Jiang ZHAO, https://orcid.org/0000-0002-9873-156X c Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2020
and network connectivity are the main concerns in the multi-UAV cooperative target tracking problem (Stachura and Frew, 2011; Lim et al., 2013; Ma and Hovakimyan
Data Loading...
