An Investigation of Models for GPS Kinematical Data Processing

Author

Lilong, Liu ; Hongyan, Wen ; Bin, Liu

Author_Institution

Dept. of Civil Eng., Guilin Univ. of Technol., Guilin, China

Volume

2

fYear

2009

fDate

18-19 July 2009

Firstpage

336

Lastpage

339

Abstract

The characteristics of three GPS kinematical data processing models, Least Square, Kalman filtering, 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 new filtering model is superior to that of LS, and that of Kalman filtering is the worst.

Keywords

Global Positioning System; Kalman filters; data handling; geographic information systems; least squares approximations; GPS kinematical data processing; Kalman filtering; data processing software; least square method; observational data; stochastic acceleration; uniform motion; Context modeling; Data processing; Equations; Filtering theory; Global Positioning System; Kalman filters; Recursive estimation; Robustness; Statistics; Stochastic processes; GPS; Kalman filtering; LS;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on

Conference_Location

Shenzhen

Print_ISBN

978-0-7695-3699-6

Type

conf

DOI

10.1109/APCIP.2009.219

Filename

5197205