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논문 기본 정보

자료유형
학술대회자료
저자정보
Sunghoon Mok (Korea Advanced Institute of Science and Technology) Mooncheon Choi (Korea Advanced Institute of Science and Technology) Hyochoong Bang (Korea Advanced Institute of Science and Technology)
저널정보
제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2011
발행연도
2011.10
수록면
1,245 - 1,250 (6page)

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초록· 키워드

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This paper studies a terrain referenced navigation which estimates a status of aircraft by using terrain elevation database and radar altimeter measurements. Terrain referenced navigation algorithm usually divides into two modes which are acquisition mode and tracking mode. In the tracking mode, states are estimated in real-time and extended Kalman filter(EKF) is a well-known navigation method for estimation. However, when conventional EKF algorithm is applied in terrain referenced navigation, estimation error can diverge because of nonlinearity of terrain elevation. To remedy this divergence problem, various nonlinear estimation techniques have been studied like stochastic linearization, bank of Kalman filters and unscented Kalman filter(UKF). In this paper, above three nonlinear estimation techniques are introduced and applied in terrain referenced navigation. Simulation results show improved navigation performance of three methods by comparing it with conventional EKF. Finally, pros and cons of each nonlinear estimation methods are analyzed by comparing their computation time and navigation performance.

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Abstract
1. INTRODUCTION
2. STRAPDOWN INS ERROR KINEMATICS
3. ORIGINAL EKF APPLICATION IN TRN
4. OTHER NONLINEAR ESTIMATION TECHNIQUES
5. SIMULATION RESULTS
6. CONCLUSION
ACKNOLEDGEMENT
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UCI(KEPA) : I410-ECN-0101-2014-569-000914551