An Information Fusion Algorithm for INS/DVL/USBL Integrated Navigation System Based on Delay State Unscented Kalman Filter

In order to reduce the impact of the lagging measurement information introduced by the high delay of underwater acoustic communication, which makes the local data out of order during fusion, a state-expanded DS-UKF is proposed under the filtering framework of UKF. Algorithm provides a new way to deal with lag measurement problem more effectively. This method first builds a filtering model for the SINS/DVL/USBL integrated navigation system, takes the centralized Kalman filter as the framework, and takes the SINS/DVL/USBL system accuracy under the ideal no-delay state as the benchmark, and uses the unscented Kalman filter as the benchmark. Based on the filter, the idea of state expansion is introduced to compensate for the measurement delay. The simulation test shows that this method can guarantee the accuracy of the navigation system after introducing random delay in the fusion system, and improve the reliability and anti-jamming performance of the integrated navigation system.