In order to solve the problem of the reduced accuracy of integrated navigation when a carrier is disturbed, a confidence check-adaptive federated Kalman filter (CC-AFKF) framework is proposed.

First, the electronic compass (EC), global positioning system (GPS) and inertial navigation system (INS) are combined. Second, a confidence check model is constructed to effectively filter out low-confidence measurements in the INS/GPS and INS/EC subsystems, and ensure the accuracy of the measured value. Finally, an adaptive adjustment factor strategy for the INS/GPS and INS/EC systems is proposed to effectively adjust system noise covariance during the update process.

A large number of related tests are carried out through an underwater vehicle equipped with INS/GPS/EC integrated navigation systems. The test results show that the CC-AFKF algorithm proposed in this paper can improve the integrated accuracy of position and velocity by at least 29% compared with typical KF and FKF algorithms.

The results of this study can provide corresponding directions and ideas for research on loosely coupled integrated navigation systems.