In the information fusion procedures of the traditional Beidou/ INS integrated navigation systems,
the correlation between the estimated sources was not considered, which could not guarantee the consistency of
information fusion, a split covariance intersection filter (split CIF)-based information fusion algorithm was
proposed. The algorithm separated the error covariance matrix into correlated part and independent part for
processing, respectively. Consistent fusion estimation was obtained by measuring information and optimal filter
gain updated in real time, which overcame the problem of the filter over-convergence caused by the fusion correlation
data. in addition, in high precision integrated navigation, the lever arm error is an important error
source. The accuracy of navigation positioning results could decrease severely for Beidou/ INS integrated navigation
systems. In this paper, the method of static lever arm measurement and error compensation for INS
update information was used to reduce the influence of lever arm effect and further to improve the positioning
accuracy. The simulation results showed that split CIF considering lever arm error compensation had good
accuracy for lever arm estimation and high navigation accuracy. The maximum error accuracy of east velocity
was 0. 041 m / s, and the maximum accuracy of latitude error was 0. 495 m. Compared with the compensated
Kalman filter, it increased by 45. 8% and 34. 0%, and compared with EKF, the error accuracy increased by
55. 1% and 10. 0%, respectively.