关键词: 半和改正模型, 定位算法, 非差分模型, 高阶容积卡尔曼滤波, 矩阵对角化变换, 定位精度

Abstract: To improve the accuracy and stability of the BDS/GPS combined positioning system, the high-degree cubature Kalman filter (CKF) is applied to the estimation of the positioning parameters, and the diagonalization of matrix (DM) transformation is used to replace the Cholesky decomposition in the standard high degree CKF. Through the DM transformation, the square root matrix of the covariance matrix has more accurate state statistics and retains the characteristics of the original feature space information, and improves the filtering accuracy. The covariance matrix of DM transformation does not require positive definite, so the stability of filtering is enhanced. The test results show that the filtering algorithm is effective and feasible for improving the positioning accuracy and stability.

Key words: semi-correcting model, positioning algorithm, non-differential model, high-degree cubature Kalman filter (HCKF), matrix diagonalization, positioning accuracy