Abstract: In traditional SINS/GNSS/CNS federal filter, the master filter and the local filters have the same state variables. However, the attitudes information output by CNS is observable for some state components in state vector. In common SINS/CNS integrated mode, the output information of CNS needs to be converted to navigation coordinate frame, which may decrease the accuracy of integrated navigation system. For the problems above, an improved SINS/GNSS/CNS federal filter based on dual quaternions is proposed. The dimension of local filter is decreased by the observability analysis of state vector, which assures the navigation accuracy and improves the real-time performance at the same time. The improved SINS/CNS integrated mode based on dual quaternions can utilize the attitudes information of CNS to integrate directly and avoid using those unobservable state components to correct SINS. Thus, the effective use of high precision CNS information is realized. The simulated results show that the proposed method has the same navigation accuracy as centralized Kalman filter, and can obtain better navigation performance when GNSS signal is lost.Key

Key words: strapdowninertialnavigationsystem, globalnavigationsatellitesystem, celestialnavigationsystem, dualquaternions, observabilityanalysis, federalfilter