SINS/GPS/CNS integrated navigation federal filtering algorithm

In view the problems during the aircraft navigation of a long-running process, such as strap-down inertial navigation system(SINS) has accumulated drift errors, GPS navigation may has signal failure, celestial navigation system(CNS) is vulnerable to environmental disturbance, and the integrated navigation system model linearization error may easily lead to filtering divergence, a SINS/GPS/CNS integrated navigation federal filtering algorithm was proposed based on the analysis of SINS, GPS and CNS. This scheme subtly combines the high precision advantage of GPS position with the high precision advantage of CNS attitude to assist SINS. The SINS errors were estimated by using a Kalman federal filter, in which the federal filtering algorithm had been effectively improved. Computer simulations demonstrate that the filter is of fast convergence, fault tolerance and high precision. The filtering precision by SINS/GPS/CNS integrated navigation can be increased by about 5% compared with that by SINS/GPS integrated navigation in position error and velocity error, and the filtering precision is increased by one order of magnitude in flat corner error. The simulation results verify the feasibility of integrated navigation scheme and the efficiency of the algorithm, showing that this integrated navigation algorithm is valuable in the engineering application.