In the integrated navigation system with inertial base, the update frequency of Strapdown Inertial Navigation System (SINS) is\nalways higher than those of aided navigation systems; thus updating inconsistency among subsystems becomes an issue.The analysis\nindicates that the state transition matrix in Kalman filter is essentially a function of carrier motion. Based on this understanding,\na simplified Kalman filter algorithm for integrated navigation is designed for those carriers with low-dynamic motions. With this\nsimplified algorithm, when the filter is without aided information updating, only calculation and accumulation on state transition\nmatrix are executed, and when the filter is with updating, normal time and measurement update are done based on the averaged\nstate transition matrix. Thus the calculation load in the simplified algorithm will be significantly lessened. Furthermore, due\nto cumulative sum and average operation, more accurate state transition matrix and higher fusion accuracy will arrive for the\nsmoothing effect on random noise of carrier motion parameters. Simulation and test results indicate that when the carrier is\nwith a low-dynamic motion, the simplified algorithm can complete the data fusion of integrated system effectively with reduced\ncomputation load and suppressed oscillation amplitude of state vector error.
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