Abstract
Inertial Navigation Systems typically rely on aiding-sensors such as GPS (Global Positioning System) to estimate the location of the system. The navigational performance of the Inertial Navigation System can be severely degraded when the GPS measurements are inaccurate or unavailable. Terrain-Aided Navigation is another method of localizing the platform by correlating the measured terrain information with a Digital Terrain Model. This paper presents an efficient Terrain-Aided Navigation method of generating position measurements from the visual appearance of the horizon profile (and hence terrain) surrounding the platform. An optimization process is used to align the measured horizon profile to an off-line pre-generated terrain-aided reference profile which allows for efficient position and attitude estimation. Numerical simulations are presented to evaluate the effectiveness of the proposed method. These results show that precise real-time attitude and position estimation is achievable using visual horizon profile information.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Kayton, M., Fried, W.: Avionics Navigation Systems. A Wiley-Interscience publication, Wiley (1997)
Bekir, E.: Introduction to Modern Navigation Systems. World Scientific (2007)
Titterton, D., Weston, J.: Strapdown Inertial Navigation Technology, 2nd edn. IEE Radar Series, The Institution of Engineering and Technology (2004)
Grewal, M., Weill, L., Andrews, A.: Global Positioning Systems, Inertial Navigation, and Integration. Wiley (2007)
Groves, P.: Principles of GNSS, inertial, and multi-sensor integrated navigation systems. GNSS Technology and Applications Series, Artech House (2008)
Farrell, J.: Aided Navigation: GPS with High Rate Sensors. McGraw-Hill professional engineering: Electronic engineering, McGraw-Hill (2008)
Mondragón, I.F., Campoy, P., Martinez, C., Olivares, M.: Omnidirectional vision applied to unmanned aerial vehicles (uavs) attitude and heading estimation. Robot. Auton. Syst. 58(6), 809–819 (2010)
Woo, J., Son, K., Li, T., Kim, G., Kweon, I.: Vision-based UAV navigation in mountain area. In: IAPR Conference on Machine Vision Applications (2007)
Naval, P.: Camera pose estimation by alignment from a single mountain image. In: International Symposium on Intelligent Robotic Systems, pp. 157–163 (1998)
Cozman, F., Krotkov, E.: Position estimation from outdoor visual landmarks for teleoperation of lunar rovers. In: Proceedings 3rd IEEE Workshop on Applications of Computer Vision, pp. 156–161 (1996)
Naval, P., Mukunoki, M., Minoh, M., Ikeda, K.: Estimating camera position and orientation from geographical map and mountain image. In: 38th Research Meeting of the Pattern Sensing Group, Society of Instrument and Control Engineers, pp. 9–16 (1997)
Talluri, R., Aggarwal, J.: Position estimation for an autonomous mobile robot in an outdoor environment. IEEE Trans. Robot. Autom. 8(5), 573–584 (1992)
Stein, F., Medioni, G.: Map-based localization using the panoramic horizon. In: IEEE International Conference on Robotics and Automation, vol. 3, pp. 2631–2637 (1992)
Thompson, W., Pick Jr, H.: Vision-based navigation. In: DARPA Image Understanding Workshop, pp. 149–152 (1992)
Thompson, W., Henderson, T., Colvin, T., Dick, L., Valiquette, C.: Vision-based localization. In: DARPA Image Understanding Workshop, pp. 491–498 (1993)
Baker, W., Clem, R.: Terrain contour matching [TERCOM] primer. Tech. Rep. ASP-TR-77-61, Wright-Patterson AFB Aeronautical Systems Division (1977)
Cowie, M., Wilkinson, N., Powlesland, R.: Latest developments of the TERPROM digital terrain system (dts). In: IEEE/ION Position, Location and Navigation Symposium, pp. 1219–1229 (2008)
Kubota, T., Moesl, K., Nakatani, I.: Map matching scheme for position estimation of planetary explorer in natural terrain. In: IEEE International Conference on Robotics and Automation, pp. 3520–3525 (2007)
Sim, D., Park, R., Kim, R., Lee, S., Kim, I.: Integrated position estimation using aerial image sequences. IEEE Trans. Pattern Anal. Mach. Intell. 24(1), 1–18 (2002)
Sim, D., Park, R.: Localization based on DEM matching using multiple aerial image pairs. IEEE Trans. Image Process. 11(1), 52–55 (2002)
Lerner, R., Rivlin, E., Rotstein, H.: Pose and motion recovery from feature correspondences and a digital terrain map. IEEE Trans. Pattern Anal. Mach. Intell. 28(9), 1404–1417 (2006)
Lerner, R., Rivlin, E., Rotstein, P.: Error analysis for a navigation algorithm based on optical-flow and a digital terrain map. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 604–610 (2004)
Moe, A.: Passive aircraft altitude estimation using computer vision, thesis, Linkoping Studies in Science and Technology (2000)
Lee, D., Kim, Y., Bang, H.: Vision-based terrain referenced navigation for unmanned aerial vehicles using homography relationship. J. Intell. Robot. Syst. 69, 489–497 (2013)
Kim, Y., Lee, D., Bang, H.: Vision-only uav navigation aided by terrain elevation map. In: International Conference on Control, Automation and Systems, pp. 1729–1733 (2012)
Nordlund, P.-J., Gustafsson, F.: Recursive estimation of three-dimensional aircraft position using terrain-aided positioning. In: International Conference on Acoustics, Speech, and Signal Processing, vol. 2, pp. II–1121–II–1124 (2002)
Nordlund, P.-J., Gustafsson, F.: Marginalized particle filter for accurate and reliable terrain-aided navigation. Trans. Aerosp. Electron. Syst. 45(4), 1385–1399 (2009)
Yigit, H., Yilmaz, G.: Development of a gpu accelerated terrain referenced uav localization and navigation algorithm. J. Intell. Robot. Syst. 70(1–4), 477–489 (2013)
Carlson, G., Bair, G., Benoit, C.: Horizon profile checkpoints for low-altitude aircraft. IEEE Trans. Aerosp. Electron. Syst. 2, 152–161 (1976)
Carlson, G., Bair, G., Benoit, C.: Geographic orientation for low-altitude aircraft using horizon matching. Tech. Rep., Defense Technical Information Center (1975)
Baboud, L., Cadík, M., Eisemann, E., Seidel, H.-P.: Automatic photo-to-terrain alignment for the annotation of mountain pictures. In: Conference on Computer Vision and Pattern Recognition, pp. 41–48 (2011)
Baatz, G., Saurer, O., Köser, K., Pollefeys, M.: Large scale visual geo-localization of images in mountainous terrain. In: Computer Vision–ECCV 2012, pp. 517–530. Springer (2012)
Imagery, N., Agency, M.: Department of defense world geodetic system 1984: its definition and relationships with local geodetic systems. Tech. Rep. TR8350.2, National Imagery and Mapping Agency (2000)
Forsyth, D., Ponce, J.: Computer Vision: A Modern Approach. Prentice Hall (2011)
Holland, P.W., Welsch, R.E.: Robust regression using iteratively reweighted least-squares. Commun. Stat. Theory Methods 6(9), 813–827 (1977)
Rey, W.: Introduction to robust and quasi-robust statistical methods. Springer-Verlag (1983)
Marquardt, D.: An algorithm for least-squares estimation of nonlinear parameters. J. Soc. Ind. Appl. Math. 11(2), 431–441 (1963)
Dumble, S., Gibbens, P.: Horizon profile detection for attitude determination. J. Intell. Robot. Syst. 68, 339–357 (2012)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Dumble, S.J., Gibbens, P.W. Efficient Terrain-Aided Visual Horizon Based Attitude Estimation and Localization. J Intell Robot Syst 78, 205–221 (2015). https://doi.org/10.1007/s10846-014-0043-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10846-014-0043-8