Design of A Filtering Algorithm Based on FOG SINS /GPS/DR

Ke Zhang; Jun Qing Bai; Bing Lun Gu

doi:10.4028/www.scientific.net/AMM.367.499

Paper Titles

A Neural Network Model for Phoneme Generation
p.478

Study on Efficiency of the Search Engine Spiders Crawl the Page
p.484

Study on Real-Time Dynamic Effects in the Search Engine
p.489

An Analysis of Impacts of Computer Network on Marketing of Furniture Enterprises
p.495

Design of A Filtering Algorithm Based on FOG SINS /GPS/DR
p.499

Analytic Solution to a Virus Infection Model
p.503

Research on Reginal Agricultural Information Technology System Construction - Take Shandong Province as Example
p.508

A Study on Grid-Based Geography Visualization Environment
p.513

Design of Locomotive Network Test Platform Based on WorldFIP
p.518

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 367Design of A Filtering Algorithm Based on FOG SINS...

Design of A Filtering Algorithm Based on FOG SINS /GPS/DR

Abstract:

As the most important index, the navigation accuracy and reliability is used to measure the performance of FOG vehicle integrated navigation system. In the foundation of federated filter and systematic accident diagnose algorithms, a novel integrated navigation filtering algorithm is designed based on FOG SINS(Fiber Optic Gyroscope Strapdown Inertial Navigation System)、GPS(Global Positioning System)、DR(Dead Reckoning). The simulation results show that the federated filter with failure detection can make full use of information from navigation sensor, and can isolate fault sources effectively, its accuracy and reliability are better than the generalized filters’.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 367)

Pages:

499-502

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.367.499

Citation:

Cite this paper

Online since:

August 2013

Authors:

Ke Zhang, Jun Qing Bai, Bing Lun Gu

Keywords:

Federated Filtering Algorithm, FOG SINS/GPS/DR

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Qin Yongyuan, Zhang Hongyue, Wang Shuhua. Kalman filtering and integrated navigation principles [M]. Xi'an North-western Polytechnical University Press, 1998 , 33-50.

Google Scholar

[2] LU Zhi-dong, WANG Lei, In-flight calibration method for SINS[J]. Journal of Chinese Inertial Technology, 2007, 4(2) 136-138.

Google Scholar

[3] IEEE standard specification format guide and test procedure for single-axis interferometric fiber optic gyros. IEEE STD 952-1997. Sponsor by Gyro and Acceler Panel of the IEEE Aero- space and Electronic Systems Society.

DOI: 10.1109/ieeestd.1998.86153

Google Scholar

[4] Li-Yuting, Sun-Fuping, Zhu-Xinhui, The development of fiber optic gyroscope and its application prospects in inertial navigation , Surveying and mapping engineering , ，2005, 14（1）：41-43.

Google Scholar

[5] Calson N.A. Federated Kalman Filter Simulation Results. Journal of theInstitute of Navigation，1994，41：297321.

Google Scholar

[6] Jiang Y F. Error analysis of analytic coarse alignment methods[J]. IEEE Trans A.E., 1998, 34(1): 334337.

Google Scholar

[7] Greg Welch, Gary Bishop. An Introduction to the Kalman Filter. TR 95-041, Chapel Hill, NC: University of North Carolina at Chapel Hill，(2004).

DOI: 10.28920/dhm52.2.136-148

Google Scholar

[8] Sage A P，Husa G W. Adaptive Filtering with Unknown Prior Statistics, Proceedings of Joint Automatic Control Conference, 1969：760769.

Google Scholar

[9] Alison Brown. Navigation Using LINK-16 GPS-INS Integration. Proceedings of IONGPS 2003, Portland , Oregon, September 2003 17.

Google Scholar

[10] Meskin D G, Bar-Itzhack I Y. Observability analysis of piece-wise constant systems, Part 1: Theory. IEEE Trans on Aerospace and Electronic Systems, 1991, 28 (4) : 10561067.

DOI: 10.1109/7.165367

Google Scholar