BeiDou/SINS tightly-coupled integrated navigation algorithm based on federated squared-root CKF

Abstract

In order to improve the fault tolerance and the running speed of BeiDou/SINS tightly-coupled integrated navigation algorithm, a BeiDou/SINS tightly-coupled navigation algorithm base on federated squared-root cubature Kalman (SRCKF) is proposed in this paper. The square root of the error covariance matrix is used to ensure the non-negative nature of the matrix in SRCKF, which avoids the divergence of the filtering result in CKF. The federated SRCKF filter is designed to fuse the attitude information, pseudorange information and pseudorange rate information from accelerometer, gyroscope, magnetic sensor and BeiDou satellite navigation receiver. Fault tolerance of the federated filter is better than that of the centralized filter. The simulation results show that the real-time performance of the proposed algorithm is better than the centralized SRCKF under the premise of ensuring navigation accuracy.