An Observable Degree-based Adaptive Federated Filtering for Bionic Integrated Navigation

Reliability is a pivotal problem in the bionic integrated navigation. To improve the accuracy and reliability of the inertial/polarization skylight/geomagnetic integrated navigation system suffering from abnormal data, an adaptive federated filter (AFF) based on observable degree is proposed. In this method, the observable degree is used to update time- varying information sharing factor. Particularly, it is used to dynamically adjust the measurement update process of the subfilter and the feedback weight of the main filter. On the basis of AFF, the integrated architecture of the bionic integrated navigation system is designed. Finally, the effectiveness of the proposed AFF is verified by simulation. The accuracy, stability of the bionic integrated navigation system can be effectively improved under abnormal sensor data.