To improve the reliability of the integrated navigation system, an improved fault detection and information fusion method is proposed for the fault-tolerant mechanism of the integrated navigation system. Designed an improved sequential probability ratio test method, introduced a fading factor to improve the tracking speed of residual information at the current time, combined with Mahalanobis distance to determine the end time of the fault, and fully reset the judgment information at the appropriate time based on the judgment result; A self-adaptive normalization fusion algorithm based on federated filtering was designed to construct normalized detection values of fault detection statistics, which were used as weight coefficients for the measurement noise variance matrix. The corresponding sub filters were weighted and updated to change the weight allocation in the global fusion process. The results of the in vehicle experiment show that the improved fully reset sequential probability ratio test algorithm has improved the positive detection rate of soft fault detection by 96.43%, 25.00%, and 19.57% respectively compared to the traditional residual chi square test, fading sequential probability ratio, and fast reset sequential probability ratio methods. The adaptive normalization fusion algorithm used also improved the positioning accuracy by 44.70% and 35.60% compared to the traditional federated filtering method. Therefore, the two improved methods can greatly enhance the fault tolerance performance of the integrated navigation system and have high practical value.