Computer Science ›› 2022, Vol. 49 ›› Issue (4): 302-311.doi: 10.11896/jsjkx.210200106

• Computer Network • Previous Articles     Next Articles

Cooperation Localization Method Based on Location Confidence of Multi-UAV in GPS-deniedEnvironment

SHI Dian-xi1,2,3, LIU Cong1, SHE Fu-jiang2, ZHANG Yong-jun2   

  1. 1 School of Computer Science, National University of Defense Technology, Changsha 410073, China;
    2 National Innovation Institute of Defense Technology, Academy of Military Sciences, Beijing 100166, China;
    3 Tianjin Artificial Intelligence Innovation Center, Tianjin 300457, China
  • Received:2021-02-13 Revised:2021-08-13 Published:2022-04-01
  • About author:SHI Dian-xi,born in 1966,Ph.D,professor,Ph.D supervisor,is a member of IEEE.His main research interests include distributed object middleware technology,adaptive software technology,artificial intelligence and robot ope-ration systems.ZHANG Yong-jun,born in 1966,Ph.D,professor.His main research interests include artificial intelligence,multi-agent cooperation,machine learning and feature recognition.
  • Supported by:
    This work was supported by the National Key Research and Development Program of China (2017YFB1001901).

Abstract: The localization of unmanned aerial vehicle (UAV) in GPS-denied environment is a difficult problem to be studied and solved.In this paper, the cooperative localization (CL) of UAV cluster system in GPS-denied environment is the main research points.Firstly, location confidence (LC) is proposed for the quantification of UAV's localization accuracy in GPS-denied environment.Secondly, a LC-based CL method, which can adaptively adjust the cooperative weight of each UAV through persistent excitation-based relative localization, is proposed to improve the accuracy of UAV cluster localization.Thirdly, a expand kalman filtering (EKF) is designed for UAV attitude calculation, which can be equipped in each UAV and used to fusing multi heterogeneous sensor data and the CL output.Finally, a multi-UAV cooperative localization system is implemented on ROS, and is verified in multi-UAV flight simulation scene of Gazebo.The simulation results show that the LC-based CL method can effectively alleviate the error accumulation of traditional inertial navigation system, and improve the accuracy of UAV cluster localization.

Key words: Cooperative localization, Expand kalman filtering, GPS-denied environment, Location confidence, Unmanned aerial vehicle

CLC Number: 

  • TP391
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