Robust multiple update-rate Kalman filter for new generation navigation signals carrier tracking

With the development of Global Navigation Satellite Systems, different types of signals and sensors, such as pilot and data signals and inertial measurement unit observations, will be fused in one tracking loop to achieve better performance. The update-rates of those measurements may be different. This issue cannot be dealt by the conventional dual update-rate phase locked loop (DUPLL) technique. To solve this problem, a generalized model called multiple update-rate Kalman filter (MUKF) is explored; it can fuse multiple update-rates measurements in one tracking loop. To improve the robustness of MUKF in challenging environments such as indoors, a robust MUKF (RMUKF) based on an adaptive factor of a three-segment function is designed. The adaptive factor can adjust the contribution of different measurements on the fusion loop automatically and improve the robustness performance. Simulation and experimental results show that the RMUKF has better performance than the DUPLL in terms of robustness and sensitivity.