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Terrain Slope Estimation Methods Using the Least Squares Approach for Terrain Referenced Navigation
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 Title & Authors
Terrain Slope Estimation Methods Using the Least Squares Approach for Terrain Referenced Navigation
Mok, Sung-Hoon; Bang, Hyochoong;
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This paper presents a study on terrain referenced navigation (TRN). The extended Kalman filter (EKF) is adopted as a filter method. A Jacobian matrix of measurement equations in the EKF consists of terrain slope terms, and accurate slope estimation is essential to keep filter stability. Two slope estimation methods are proposed in this study. Both methods are based on the least-squares approach. One is planar regression searching the best plane, in the least-squares sense, representing the terrain map over the region, determined by position error covariance. It is shown that the method could provide a more accurate solution than the previously developed linear regression approach, which uses lines rather than a plane in the least-squares measure. The other proposed method is weighted planar regression. Additional weights formed by Gaussian pdf are multiplied in the planar regression, to reflect the actual pdf of the position estimate of EKF. Monte Carlo simulations are conducted, to compare the performance between the previous and two proposed methods, by analyzing the filter properties of divergence probability and convergence speed. It is expected that one of the slope estimation methods could be implemented, after determining which of the filter properties is more significant at each mission.
Terrain referenced navigation;Extended Kalman filter;Terrain Slope Estimation;Least squares method;
 Cited by
자율무인잠수정의 지형참조항법 연구,목성훈;방효충;권재현;유명종;

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