Paper Title:
Compare and Analysis of Kalman and H∞ Filtering Algorithms in GNSS Vehicle Navigation Data Filtering
  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.

  Info
Periodical
Chapter
Chapter 7: Traffic Control and Information Technology
Edited by
Shucai Li
Pages
964-970
DOI
10.4028/www.scientific.net/AMM.97-98.964
Citation
J. Sun, J. P. Xing, Y. Wu, Z. L. Ma, Y. B. Wu, "Compare and Analysis of Kalman and H∞ Filtering Algorithms in GNSS Vehicle Navigation Data Filtering", Applied Mechanics and Materials, Vols. 97-98, pp. 964-970, 2011
Online since
September 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Guang Qian Chu, Yan Cao, Chao Liang Si
Abstract:In recent years, the typhoon happens frequently. When typhoon suddenly arrives, the only way to rescue the ship which calls for help in time...
2428
Authors: Jia Xu, Qing Li
Chapter 8: System Modeling and Simulation
Abstract:The algorithms and the applications of UKF filtering of UAV MEMS Gyro based on time-series model are presented in this paper. First Gyro...
4885
Authors: Qing Hua Ji
Chapter 3: Engineering Technology
Abstract:Aiming at the high noise level with Micro-Electro-Mechanical System (MEMS) accelerometer, the Kalman filter algorithm is introduced to...
1947
Authors: Ye Li, Yan Qing Jiang
Chapter 5: Information Processing and Computational Science
Abstract:The application of distributed multi-sensor information fusion technology in accurate positioning of Underwater Vehicle was introduced in...
1006
Authors: Hai Peng Liu, Ke Zhang, Heng Nian Li
Chapter 5: Measurements, Monitoring and Sensor
Abstract:With the fast development of aviation industry, integrated navigation techniques must be improved quickly along with it. In order to overcome...
1239