Fast data fusion method for integrated navigation system and hardware in loop simulation

The main factor in determining the computation time of Kalman filter is the dimension of the model state vector. The number of computations per iteration is direct proportion of n cube. Any reduction in the number of states will significantly decrease the computation time. Since 70 percent of the filtering calculation task is the forecast equation of covariance matrix, the method of reduced-dimension model and matrix product is applied in the micro inertial measurement unit/global positioning system/micro magnetic compass (MIMU/GPS/MMC) integrated navigation system, and the hardware in the loop simulation results based on the microprocessor proves that the method not only can provide satisfactory accuracy for aircraft navigation but also can reduce the filtering calculation.