Affiliation:
1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
2. School of Internet of Things, Nanjing University of Posts and telecommunications
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.
Funder
Shanghai Aerospace Science and Technology Innovation Fund
National Natural Science Foundation of China
Natural Science Fund of Jiangsu Province
advanced research project of the equipment development
Subject
Computer Networks and Communications,General Engineering
Cited by
10 articles.
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