A New Adaptive Federated Cubature Kalman Filter Based on Chi-Square Test for SINS/GNSS/SRS/CNS Integration

As an emerging means of transportation for the intelligent transportation system (ITS) in aviation and aerospace, hypersonic cruise vehicles (HCVs) have received numerous research interests during the past several decades. However, the navigation and positioning strictly limit the progress and application of HCVs due to their special characteristics on dynamics and environments. To improve the stability of navigation in HCVs, a chi-square test-based adaptive federated cubature Kalman filter (CAFCKF) is proposed in this paper. In the proposed approach, the chi-square test is adopted for the estimation of the measurement noise statistics firstly. Subsequently, a new adaptive information fusion factor is designed for the federated filter to adjust the contribution of each subsystem. Finally, the information sharing factor, which is used for the amendment of the state covariance of each subsystem, is refined based on the judging index of the chi-square test accordingly. Simulation results show that the proposed CAFCKF can be used to improve the accuracy and stability of the navigation system.