Compare and analysis of Kalman and H∞ filtering algorithms in GNSS vehicle navigation data filtering

Juan Sun, Jianping Xing, Yong Wu, Zhenliang Ma, Yubing Wu

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

Abstract

In the actual process of navigation, signal interference and inaccurate tracking model can cause inaccurate positioning of navigation. Various filtering algorithms are needed to filter out the interference and improve precision. First of all, this paper elaborates and compares Kalman filtering algorithms and H∞ filtering algorithm, which are both applied in filtering GNSS navigation data. After that, some datas are selected from the vehicle navigation data as the source datas. In the meantime, depend on the ideal model, factors are added into it in consideration of practical application. As a result, the mathematical models for Kalman and H∞ are established. According to the filter algorithm and the mathematic model, simulation programs and their flow charts of Kalman filtering algorithm and H∞ filtering algorithm are all accomplished. Finally, it shows the results of simulation and analyses the problems appeared.

Original languageEnglish
Title of host publicationAdvanced Transportation
Pages964-970
Number of pages7
DOIs
Publication statusPublished - 13 Oct 2011
Event2011 International Conference on Civil Engineering and Transportation, ICCET 2011 - Jinan, China
Duration: 14 Oct 201116 Oct 2011

Publication series

NameApplied Mechanics and Materials
Volume97-98
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference2011 International Conference on Civil Engineering and Transportation, ICCET 2011
CountryChina
CityJinan
Period14/10/1116/10/11

Keywords

  • GNSS
  • H∞filter
  • Kalman filter
  • Simulation program

Cite this

Sun, J., Xing, J., Wu, Y., Ma, Z., & Wu, Y. (2011). Compare and analysis of Kalman and H∞ filtering algorithms in GNSS vehicle navigation data filtering. In Advanced Transportation (pp. 964-970). (Applied Mechanics and Materials; Vol. 97-98). https://doi.org/10.4028/www.scientific.net/AMM.97-98.964