제어로봇시스템학회:학술대회논문집
- 2003.10a
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- Pages.984-989
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- 2003
GPS/INS Integration using Fuzzy-based Kalman Filtering
- Lim, Jung-Hyun (Department of Aerospace Engineering, Sejong University) ;
- Ju, Gwang-Hyeok (Navigation & Control Group, KARI) ;
- Yoo, Chang-Sun (Smart UAV Development Center) ;
- Hong, Sung-Kyung (Department of Aerospace Engineering, Sejong University) ;
- Kwon, Tae-Yong (National Star Inc.) ;
- Ahn, Iee-Ki (Navigation & Control Group, KARI)
- Published : 2003.10.22
Abstract
The integrated global position system (GPS) and inertial navigation system (INS) has been considered as a cost-effective way of providing an accurate and reliable navigation system for civil and military system. Even the integration of a navigation sensor as a supporting device requires the development of non-traditional approaches and algorithms. The objective of this paper is to assess the feasibility of integrated with GPS and INS information, to provide the navigation capability for long term accuracy of the integrated system. Advanced algorithms are used to integrate the GPS and INS sensor data. That is fuzzy inference system based Weighted Extended Kalman Filter(FWEKF) algorithm INS signal corrections to provided an accurate navigation system of the integrated GPS and INS. Repeatedly, these include INS error, calculated platform corrections using GPS outputs, velocity corrections, position correction and error model estimation for prediction. Therefore, the paper introduces the newly developed technology which is aimed at achieving high accuracy results with integrated system. Finally, in this paper are given the results of simulation tests of the integrated system and the results show very good performance