Relative Position-Based Collaborative Navigation for Cluster UAVs

The inertial equipment carried by UAVs without satellite signal assistance will accumulate errors over time, which cannot meet the requirement of obtaining high-precision cluster navigation information for cluster UAVs in long-duration flights. Aiming at this problem, a scheme for cooperative navigation of cluster UAVs based on relative position assistance is proposed. Firstly, the state equations of the cooperative navigation system are established by modeling the errors of inertial devices of low-precision UAVs; secondly, the relative position information of low-precision UAVs and high-precision UAVs as well as other low-precision UAVs transmitted between UAVs through the data chain is taken as the observation equation; finally, the inertial errors of low-precision UAVs are compensated by using the traceless Kalman filtering for the error compensation, which improves the navigation accuracy. After 30 min simulation results show that the cooperative navigation scheme converges the velocity and position errors of the low-precision UAV to 0.5 m/s and 5 m, respectively, which improves the navigation accuracy greatly.