The Expanded Central Difference Filter for GNSS with Unknown State Dynamics
【摘要】：In this paper, a novel filtering method, i.e., the expanded central difference filter, was established for global navigation satellite systems (GNSS) navigation. The approach involved modelling an expanded state space model by adopting the polynomial predictive idea and state dimension expansion. The new model was established without the exact knowledge of the original state dynamics, i.e., no matter we knew the original state propagation well or not, which was common in practice. A correspondent expanded state space central difference filter (ECDF) was then presented based on the proposed model. The simulation results of the GPS navigation demonstrated that the proposed method did work better than the existed central difference filter (CDF), especially when the state dynamics were not known well.