Abstract
Extended Kalman Filtering (EKF) based GPS-INS has poor performance when there are strong nonlinearities and the measurements are corrupted by noise or outliers. This paper proposes a Contemplative Realtime (CRT) framework for tightly coupled Differential GPS aided inertial navigation. This method guarantees low latency for real-time application and meanwhile enhances the accuracy and reliability of navigation. To realize these improvements, a Bayesian optimization based smoothing is combined with conventional filtering in an efficient way. For demonstration purpose, this CRT framework is implemented on an automotive vehicle with differential pseudorange and IMU measurements. The implementation result shows that compared to standard EKF method, the proposed approach could provide accurate vehicle navigation with robustness.
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