Sequential Filtering Fusion Algorithm for Marine Integrated Navigation System
GE Quan-bo · Navigation of China · 2008
Neither centralized fusion nor distributed fusion in marine integrated navigation system can have both high filtering precision and good computation performance fault-tolerance.Moreover,it is too idealized to model vessel process noise with white noise neglecting the impacts of marine environments on ship motions.For these problems,a sequential filtering fusion algorithm for marine integrated navigation system is presented.In the new algorithm vessel process noise is modeled with 1st order Markov process,the state equations are converted into the basic equations of standard Kalman filter with state dimension augmentation method,then the effectiveness of each sub navigation system is checked and fusions of all effective data are carried out step by step for positioning the vessel.Compared with traditional sequential filtering fusion algorithms,the new algorithm has the same filtering precision and good computation performance as the centralized fusion algorithm,with the additional advantage of practicability and better fault-tolerance.Theoretical analysis and simulation results of a vessel GPS/SINS integrated navigation system demonstrate the effectiveness and superiority of the new algorithm.