INS - GPS COMBINATION AND PERFORMANCE IMPROVEMENT USING ADAPTIVE FUZZY KALMAN FILTER

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

HAVANGI R.; TESHNEHLAB M.; GHANBARPOUR ASL HABIB

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: MODARES TECHNICAL AND ENGINEERING Year:2004 | Volume:- | Issue:16 Page(s): 67-80

Download Full-Text

Persian Verion

View:

2,287

Download:

Cites:

Information Journal Paper

Title

INS - GPS COMBINATION AND PERFORMANCE IMPROVEMENT USING ADAPTIVE FUZZY KALMAN FILTER

Author(s)

HAVANGI R. | TESHNEHLAB M. | GHANBARPOUR ASL HABIB | Issue Writer Certificate

Keywords

GPSQ2

INSQ4

COMBINATIONQ4

KALMAN FILTERQ2

ADAPTIVE FUZZY KALMAN FILTERQ4

Abstract

The error of inertial navigation systems increase versus time, therefore for achieving higher accuracy specially in long time navigations we have to use an aiding system. Global positioning system is the best aiding system in this case. In this paper we first simulate a GPS and INS; Then simulate tightly integration and finally review adaptation method of KALMAN FILTERing a Fuzzy adaptive KALMAN FILTER is proposed in which adaptation is accomplished by adaptive tuning of covariance matrix of measurement noise (R) and process noise (Q). We have achieved adaptive tuning using Fuzzy systems and Covariance - Matching techniques .The results show that the adaptive fuzzy integration of GPS and INS would lead to better performance comparing to the usual methods of integration in which both R and Q matrices are constant.

Cites

No record.

References

No record.

Cite

APA: Copy

HAVANGI, R., TESHNEHLAB, M., & GHANBARPOUR ASL, HABIB. (2004). INS - GPS COMBINATION AND PERFORMANCE IMPROVEMENT USING ADAPTIVE FUZZY KALMAN FILTER. MODARES TECHNICAL AND ENGINEERING, -(16), 67-80. SID. https://sid.ir/paper/24976/en

Vancouver: Copy

HAVANGI R., TESHNEHLAB M., GHANBARPOUR ASL HABIB. INS - GPS COMBINATION AND PERFORMANCE IMPROVEMENT USING ADAPTIVE FUZZY KALMAN FILTER. MODARES TECHNICAL AND ENGINEERING[Internet]. 2004;-(16):67-80. Available from: https://sid.ir/paper/24976/en

IEEE: Copy

R. HAVANGI, M. TESHNEHLAB, and HABIB GHANBARPOUR ASL, “INS - GPS COMBINATION AND PERFORMANCE IMPROVEMENT USING ADAPTIVE FUZZY KALMAN FILTER,” MODARES TECHNICAL AND ENGINEERING, vol. -, no. 16, pp. 67–80, 2004, [Online]. Available: https://sid.ir/paper/24976/en

Related Journal Papers