Multi-UAV Cooperative Navigation Algorithm Based on Federated Filtering Structure

Navigation error of each UAV with low-precision navigation devices in UAV formation will increase rapidly over time, and centralized Kalman filtering in cooperative navigation will lead to a sharp increase in the amount of calculations for a single machine. A UAV cooperative navigation algorithm based on federated filtering structure is proposed aiming at these problems. Firstly, the state model of each sub-filter is established, and the measurement model of the sub-filter is constructed based on the output information and the relative navigation information of the navigation system. Secondly, the main filter measurement equation is constructed by the joint error correction of the UAV navigation systems. The federal filtering structure is used to estimate the error of each UAV navigation system and the Kalman filter is improved. Simulation results show that this algorithm can effectively slow down the divergence of navigation errors in each UAVs and compared with the centralized filter reduce the computation of leader.