A hybrid cooperative navigation method for UAV swarm based on factor graph and Kalman filter. (January 2022)

• Record Type: Journal Article
• Authors: Chen, Mingxing; Xiong, Zhi; Xiong, Jun; Wang, Rong
• Is Part Of: International journal of distributed sensor networks. Volume 18:Number 1(2022)
• Publication Date: 2022-01
• Subjects: Cooperative navigation -- factor graph -- Kalman filter -- UAV swarm; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/15501477211064758
• Languages: English
• ISSNs: 1550-1329

Abstract

Navigation plays an important role in the task execution of the micro-unmanned aerial vehicle (UAV) swarm. The Cooperative Navigation (CN) method that fuses the observation of onboard sensors and relative information between UAVs is a research hotspot. Aiming at the efficiency and accuracy problems of previous studies, this article proposes a hybrid-CN method for UAV swarm based on Factor Graph and Kalman filter. A global Factor Graph is used to combine Global Navigation Satellite System (GNSS) and ranging information to provide position estimations for modifying the distributed Kalman filter; distributed Kalman filter is established on each UAV to fuse inertial information and optimized position estimation to modify the navigation states. In order to provide time-consistent GNSS position information for the Factor Graph, a time synchronization filter is designed. The proposed method is tested and verified using standard Monte Carlo simulations, simulation results show that it can provide a more precise and efficient CN solution than traditional CN methods.