A nonlinear quaternion-based fault-tolerant SINS/GNSS integrated navigation method for autonomous UAVs

The fault-tolerant integrated navigation methods using strapdown inertial navigation system (SINS) and global navigation satellite system (GNSS) for unmanned aerial vehicles (UAVs) are studied herein to address two types of possible faults, system fault and measurement fault. Two typical approximation-based nonlinear filters, extended Kalman filter (EKF) and divided difference Kalman filters (DDKFs), are modified to be fault-tolerant for accurate navigation even in the presence of these faults. Criteria are presented to detect the faults, and related covariance matrices of the predicted errors are enlarged using fault accommodation factors to make the faulty state or measurement components be normally treated. Navigation simulations using the nonlinear quaternion-based navigation error model are given to demonstrate the effectiveness of the proposed methods.