关键词: 联邦卡尔曼滤波, 变增益, 定位算法, 精度, 发散

Abstract: The pseudorange error worked out by the GPS receiver module is the major errors of GPS/INS navigation system, which can be weakened by using one federal Kalman filter algorithm of integrated navigation. This algorithm has two Kalman filters. The first Kalman filter filters the pseudo range and Doppler shift got from the GPS module. Then, the results got from the first Kalman filter is filtered by the second Kalman filter with the data got from the INS module. And it gets the correction and the optimum estimate. With the filter step increasing, the system prediction error variance tends to zero gradually, then the state estimation will excessively dependence on the old measurements, which will cause filter divergence and affect the position accuracy. To effectively increase the correction amount of the new measurements, this paper introduces a variable weighting factor in federal Kalman filter integrated navigation algorithm. The simulation results show that the improved variable gain federal Kalman filtering algorithm has the advantages of federal Kalman filter, and the filtering effect of this algorithm is improved obviously, which can effectively restrain the filter divergence and improve the positioning precision of the system.

Key words: federation Kalman filter, variable gain, location algorithm, accuracy, divergence