The features of carrier-based aircraft’s navigation systems during the approach and landing phases are investigated. A new adaptive Kalman filter with unknown state noise statistics is proposed to improve the accuracy of the INS/GNSS integrated navigation system. The adaptive filtering algorithm aims to estimate and adapt the unknown state noise covariance Qin high dynamic conditions, when the measurement noise covariance Ris assumed to be known empirically in advance. The new adaptive Kalman filter based on the innovation sequence and pseudo-measurement vector approach makes it more effective to estimateandadapt Q. The simulation results and semi-physical experiments show that the application of the proposed adaptive Kalman filter can guarantee a higher estimation accuracy of the state variables.