Advanced SearchSearch Tips
Terrain Slope Estimation Methods Using the Least Squares Approach for Terrain Referenced Navigation
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Terrain Slope Estimation Methods Using the Least Squares Approach for Terrain Referenced Navigation
Mok, Sung-Hoon; Bang, Hyochoong;
  PDF(new window)
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;

제어로봇시스템학회논문지, 2013. vol.19. 8, pp.702-708 crossref(new window)
Improvement of Terrain Referenced Navigation using a Point Mass Filter with Grid Adaptation,;;

International Journal of Control, Automation, and Systems, 2015. vol.13. 5, pp.1173-1181 crossref(new window)
Improvement of terrain referenced navigation using a Point Mass Filter with grid adaptation, International Journal of Control, Automation and Systems, 2015, 13, 5, 1173  crossref(new windwow)
Terrain Referenced Navigation for Autonomous Underwater Vehicles, Journal of Institute of Control, Robotics and Systems, 2013, 19, 8, 702  crossref(new windwow)
Grid Design for Efficient and Accurate Point Mass Filter-Based Terrain Referenced Navigation, IEEE Sensors Journal, 2018, 18, 4, 1731  crossref(new windwow)
Metzger, J., Wendel, J., Trommer, G. F., Tumbragel, F., and Taddiken, B., "Hybrid Terrain Referenced Navigation System using a Bank of Kalman Filters and a Comparison Technique," AIAA Guidance, Navigation and Control Conference, Providence, Rhode Island, USA, 2004.

Bergman, N., Ljung, L., and Gustafsson, F., "Point-Mass Filter and Carmer-Rao Bound for Terrain-Aided Navigation," Conference on Decision & Control, San Diego, California, USA, 1997.

Metzger, J., Wisotzky, K., Wendel, J., and Trommer, G. F., "Sigma-Point Filter for Terrain Referenced Navigation," AIAA Guidance, Navigation, and Control Conference and Exhibit, San Francisco, California, USA, 2005.

Hostetler, L., and Andreas, R., "Nonlinear Kalman Filtering Techniques for Terrain-Aided Navigation," IEEE Transactions on Automatic Control, Vol. 28, No. 3, 1983, pp. 315-323. crossref(new window)

Mok, S. H., Choi, M., and Bang, H., "Performance Comparison of Nonlinear Estimation Techniques in Terrain Referenced Navigation," Proceedings of the 11th International Conference on Control, Automation and System, KINTEX, Gyeonggi-do, Korea, 2011, pp. 1244-1249.

Titterton, D. H., and Weston, J. L., Strapdown Inertial Navigation Technology, The Institution of Electrical Engineers, Reston, Virginia, USA, 2004, pp. 17-58.