Volume 4, Issue 1 (2004)
MJEE 2004, 4(1): 67-80 |
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HAVANGI R, TESHNEHLAB M, GHANBARPOUR ASL H. INS - GPS COMBINATION AND PERFORMANCE IMPROVEMENT USING ADAPTIVE FUZZY KALMAN FILTER. MJEE 2004; 4 (1) :67-80
URL: http://mjee.modares.ac.ir/article-17-11794-en.html
URL: http://mjee.modares.ac.ir/article-17-11794-en.html
1- K.N.T university
2- sharif university of technology
2- sharif university of technology
Abstract: (3760 Views)
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.
Received: 2003/05/1 | Accepted: 2004/07/1 | Published: 2004/09/1
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