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Comparison of Filtering Algorithms for GPS Static Point Positioning


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Comparison of Filtering Algorithms for GPS Static Point Positioning
SUN GangWANG Chang-mingZHANG Ai-jun
School of Mechanical Engineering,NUST,Nanjing 210094,China
global positioning system static point positioning Kalman filtering particle filtering extended Kalman particle filtering
P228. 4
In view of the poor precision of the low-cost GPS positioning system for the static point positioning, Kalman filtering( KF) ,particle filtering( PF) and extended Kalman particle filtering( EKPF) algorithms are respectively applied to the two positioning data sets including latitude,longitude and altitude from two different GPS-OEM boards. The performances of the filtering algorithms are compared,and the results show that the positioning accuracy is improved after applying the filters. The EKPF has the best performance,followed by the PF,and the KF only has a general effect. This result offers an effective solution to improve the positioning accuracy for the low-coast GPS static point positioning system. It verifies the theoretic perfermance of each filtering algorithm.


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Last Update: 2012-02-28