A Matching Algorithm Using Gravity Anomaly Based on the RAE Parallel Filtering

Serial observed gravity anomaly data and a gravity anomaly referenced map for navigation can be used to correct the drifting errors of inertial navigation system based on the EKF. To address the problem of unknown gravity anomaly measurement noise due to an unpredictable gravimetric environment and disturbances to the measuring instruments, et al, a matching algorithm for gravity anomaly filtering based on residual errors can be used to estimate measurement noise variance adaptively; Residual-based Adaptive Estimation (RAE). A set of parallel Kalman filters were designed and a rule for selecting the best filter was simplified. RAE filtering experimental results show that the longitude and latitude drifting errors in inertial navigation systems can be reduced effectively based on the RAE filtering and positioning accuracy of the navigation system thus improved.