Study on One Multi-Sensor Integrated Navigation System Algorithm Based on Filtering Step by Step

One of normal algorithm for multi-sensor integrated navigation system is centralized Kalman filter which has the shortcoming of heavy computation burden and bad fault-tolerant.Thus,this paper puts forward one filtering step by step algorithm for multi-sensor integrated navigation system,when the observation values of all sensors come together,firstly the system state at this time is predicted,then the conventional Kalman filter and every navigation sensor's observation are used to update the estimate value of this time's state vector in turn.Accordingly the optimal fused estimated value of this time's state vector can be obtained based on the global information.At last the GPS /SST/altimeter/SINS integrated navigation system is used to examine the above algorithm,the simulated results show that this algorithm has the same estimated precision as the centralized Kalman filter,but has lower computation burden.