Cooperative navigation of unmanned aerial vehicle formation with delayed measurement

This paper focused on the problem of positioning accuracy degradation caused by delayed measurement information in unmanned aerial vehicle (UAV) formation cooperative navigation under complex environments such as cities and hills, and presented a non-synchronous compensation algorithm based on kinematic constraints and constructed a distributed cooperative navigation filter based on the analysis of the basic operating characteristics of inertial devices, satellite receivers, and ranging sensors. In the UAV formation, the leader-UAV is equipped with real-time kinematic differential equipment and airborne data link to construct the airborne reference beacons and provide cooperative navigation services for the wingman-UAV. Firstly, the navigation filtering framework with inertial sensors as the core is established. Secondly, the non-synchronous compensation filter is constructed by using the kinematic constraint model, which compensates and corrects the non-synchronous air-based position of the leader-UAV, and reduces the effect of delayed measurement on the positioning error of the system. Then the fault diagnosis algorithm is utilized to complete the identification and rejection of abnormal range values in the case of non-line-of-sight. Finally, the navigation parameters are solved by the Kalman filter. Simulation results show that the non-synchronous compensated filtering proposed in this paper can improve the absolute positioning accuracy by 55%, which effectively improves the cooperative navigation performance and robustness under the presence of random time delay in the measurement information.