Aiming at the problem that it is difficult for cluster UAVs to function with the combination of traditional GPS and inertial navigation when satellite signals are obstructed, a cooperative navigation algorithm for cluster UAVs is designed, in which UAVs equipped with low-precision inertial devices acquire the position information of UAVs equipped with high-precision inertial devices within the cluster through a data chain, and the position, velocity, and attitude information outputted from their own low-precision inertial devices is corrected by the trace-free Kalman filter to reduce the navigation error. And attitude information to reduce the navigation error. After 1100 s simulation, the latitude and longitude errors of the low-precision UAV converge to 1 × 10−6 degrees, which is about 0.1 m, the northward and eastward velocity errors are reduced to 0.01 m/s, and the pitch, heading, and roll angle errors are less than 10% of the initial alignment error, which improves its navigation accuracy.
A Position Velocity and Attitude Error Correction Method for Cluster UAVs Based on Traceless Kalman Filter Co-navigation
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2024 ; Shenyang, China September 19, 2024 - September 21, 2024
Proceedings of 4th 2024 International Conference on Autonomous Unmanned Systems (4th ICAUS 2024) ; Kapitel : 26 ; 277-287
22.03.2025
11 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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