DocumentCode :
2237671
Title :
Estimation Methods for GPS Kinematical Positioning and Simulation Analysis
Author :
Pan Xiong ; Kang Shuangshuang ; Yuan Shuanli ; Liu Lilong
Author_Institution :
Fac. of Inf. Eng., China Univ. of Geosci., Wuhan, China
fYear :
2009
fDate :
26-28 Dec. 2009
Firstpage :
845
Lastpage :
848
Abstract :
The characteristics of three GPS kinematical data processing models, Least Square, Kalman filtering, and Semiparametric model are discussed and their advantages and disadvantages are compared. With observational data and pertinent data processing software, the applicable condition, context and effect of the three models are experimented. Results show that when the mobile platform is in uniform motion, the accuracy of the three models are almost equal; when the mobile platform is in stochastic acceleration, the accuracy of Semiparametric model is superior to that of LS, and that of Kalman filtering is the worst.
Keywords :
Global Positioning System; Kalman filters; estimation theory; least squares approximations; GPS kinematical data processing; Kalman filtering; data processing software; estimation methods; least square; mobile platform; semiparametric model; stochastic acceleration; Analytical models; Data engineering; Data processing; Equations; Filtering; Global Positioning System; Kalman filters; Least squares approximation; Recursive estimation; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
Type :
conf
DOI :
10.1109/ICISE.2009.560
Filename :
5455728
Link To Document :
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