DOI QR코드

DOI QR Code

Development of Real-Time Vision Aided Navigation Using EO/IR Image Information of Tactical Unmanned Aerial System in GPS Denied Environment

GPS 취약 환경에서 전술급 무인항공기의 주/야간 영상정보를 기반으로 한 실시간 비행체 위치 보정 시스템 개발

  • Received : 2019.12.20
  • Accepted : 2020.05.13
  • Published : 2020.06.01

Abstract

In this study, a real-time Tactical UAS position compensation system based on image information developed to compensate for the weakness of location navigation information during GPS signal interference and jamming / spoofing attack is described. The Tactical UAS (KUS-FT) is capable of automatic flight by switching the mode from GPS/INS integrated navigation to DR/AHRS when GPS signal is lost. However, in the case of location navigation, errors accumulate over time due to dead reckoning (DR) using airspeed and azimuth which causes problems such as UAS positioning and data link antenna tracking. To minimize the accumulation of position error, based on the target data of specific region through image sensor, we developed a system that calculates the position using the UAS attitude, EO/IR (Electric Optic/Infra-Red) azimuth and elevation and numerical map data and corrects the calculated position in real-time. In addition, function and performance of the image information based real-time UAS position compensation system has been verified by ground test using GPS simulator and flight test in DR mode.

본 연구에서는 전술급 무인항공기의 GPS 신호간섭 및 재밍(Jamming)/기만(Spoofing) 공격 시 위치항법 정보의 취약성을 보완하기 위해 개발한 영상정보 기반 실시간 비행체 위치보정 시스템을 기술하고자 한다. 전술급 무인항공기는 GPS 두절 시 항법장비가 GPS/INS 통합항법에서 DR/AHRS 모드로 전환하여 자동비행이 가능하나, 위치 항법의 경우 대기속도 및 방위각을 활용한 추측항법(DR, Dead Reckoning)으로 인해 시간이 지나면 오차가 누적되어 비행체 위치 파악 및 데이터링크 안테나 자동추적이 제한되는 등의 문제점을 갖고 있다. 이러한 위치 오차의 누적을 최소화하기 위해 영상감지기를 이용한 특정지역 위치보정점을 바탕으로 비행체 자세, 영상감지기 방위각/고각 및 수치지도 데이터(DTED)를 활용하여 비행체 위치를 계산하고 이를 실시간으로 항법장비에 보정하는 시스템을 개발하였다. 또한 GPS 시뮬레이터를 이용한 지상시험과 추측항법 모드의 비행시험으로 영상정보 기반 실시간 비행체 위치보정 시스템의 기능 및 성능을 검증하였다.

Keywords

References

  1. Choi, S. K., Moon, J. H. and Ko, J. S., "Airworthiness Case Study for the Tactical UAV's Flight Control System," Journal of the Korea Institute of Military Science and Technology, Vol. 17, No. 4, 2014, pp. 430-435. https://doi.org/10.9766/KIMST.2014.17.4.430
  2. Choi, S. K., Moon, J. H., Cho, S. J. and Lee, S. H., "Flight Control System Design and Flight Test of the Tactical Unmanned Aircraft System," Proceeding of The Society for Aerospace System Engineering Fall Conference, October 2014, pp. 427-432.
  3. Kim, K. Y., "Analysis of Anti-Jamming Techniques for Satellite Navigation Systems," Journal of Korean Institute of Communications and Information Sciences, Vol. 38C No. 12, 2013, pp. 1216-1227. https://doi.org/10.7840/kics.2013.38C.12.1216
  4. Golden, J. P., "Terrain contour matching (TERCOM): A cruise missile guidance aid," In Proceedings of SPIE Image Processing for Missile Guidance, Vol. 38, July-August 1980, pp. 10-18.
  5. Rodriguez, J. J. and Aggarwal, J. K., "Matching aerial images to 3-D terrain maps," IEEE Transactions on Pattern Analysis and Machine Intelligence, No. 12, December 1990, pp. 1138-1149.
  6. Mok, S. H., Bang, H. C. and Yu, M. J., "Performance Analysis of Vision-Based Terrain Referenced Navigation," Journal of Institute of Control, Robotics and Systems, Vol. 23, No. 4, 2017, pp. 294-299. https://doi.org/10.5302/J.ICROS.2017.16.0196
  7. Horn, B. K. and Schunck, B. G., "Determining Optical Flow," Artificial Intelligence, Vol. 17, Issues 1-3, 1981, pp. 185-203. https://doi.org/10.1016/0004-3702(81)90024-2
  8. Bosse, M., Karl, W. C., Castanon, D. A. and DeBitetto, P., "A vision augmented navigation system," Proceedings of the IEEE Conference on Intelligent Transportation Systems, November 9-12, 1997, pp. 1028-1033.
  9. Li, H. and Yang, S. X., "A Behavior-based Mobile Robot with a Visual Landmark-recognition System," IEEE/ASME Transactions on Mechatronics, Vol. 8, No. 3, 2003, pp. 390-400. https://doi.org/10.1109/TMECH.2003.816818
  10. Herissé, B., Hamel, T., Mahony, R. and Russotto, F., "Landing a VTOL Unmanned Aerial Vehicle on a Moving Platform Using Optical Flow," IEEE Transactions on Robotics, Vol. 28, No. 1, 2012, pp. 77-89. https://doi.org/10.1109/TRO.2011.2163435
  11. Maier, J. and Humenberger, M., "Movement Detection Based on Dense Optical Flow for Unmanned Aerial Vehicles," International Journal of Advanced Robotic Systems, Vol. 10, No. 2, 2013, p. 146. https://doi.org/10.5772/52764
  12. Cho, D. M., Tsiotras, P., Zhang, G. and Holzinger, M., "Robust Feature Detection, Acquisition and Tracking for Relative Navigation in Space with a Known Target," Proceeding of AIAA Guidance, Navigation, and Control (GNC) Conference, Boston, MA, August 19-22, 2013.
  13. Nourani-Vatani, N., Borges, P. V. K., Roberts, J. M. and Srinivasan, M. V., "On the Use of Optical Flow for Scene Change Detection and Description," Journal of Intelligent and Robotic Systems, Vol. 74, Issues 3-4, 2014, p. 817. https://doi.org/10.1007/s10846-013-9840-8
  14. DeSouza, G. N. and Kak, A. C., "Vision for Mobile Robot Navigation: A Survey," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 2, February 2002.
  15. Sim, D G., Park, R. H., Kim, R. C., Lee, S. U. and Kim, I. C., "Integrated position estimation using aerial image sequences," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, Issue 1, January 2002, pp. 1-18. https://doi.org/10.1109/34.982881
  16. Fournier, J., Ricard, B. and Laurendeau, D., "Mapping and Exploration of Complex Environments Using Persistent 3D Model," Proceeding of Fourth Canadian Conference on Computer and Robot Vision, IEEE, Montreal, Canada, May 28-30, 2007.
  17. Gutmann, J., Fukuchi, M. and Fujita, M., "3D Perception and Environment Map Generation for Humanoid Robot Navigation," The International Journal of Robotics Research, Vol. 27, No. 10, 2008, pp. 1117-1134. https://doi.org/10.1177/0278364908096316
  18. Dryanovski, I., Morris, W. and Xiao, J., "Multi-Volume Occupancy Grids: An Efficient Probabilistic 3D Mapping Model for Micro Aerial Vehicles," Proceeding of IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, China, October 18-22 2010.
  19. Zhang, J., Liu, W. and Wu, Y., "Novel Technique for Vision-Based UAV Navigation," IEEE Transactions on Aerospace and Electronic Systems, Vol. 47, Issue 4, October 2011.
  20. Hornung, A., Wurm, K. M., Bennewitz, M., Stachniss, C. and Burgard, W., "OctoMap: An Efficient Probabilistic 3D Mapping Framework Based on Octrees," Autonomous Robotics, Vol. 34, No. 3, 2013, pp. 189-206. https://doi.org/10.1007/s10514-012-9321-0
  21. Moravec, H. P., "The Stanford Cart and the CMU Rover," Proceedings of the IEEE, Vol. 71, No. 7, 1983 pp. 872-884. https://doi.org/10.1109/PROC.1983.12684
  22. Davison, A. J., "Real-Time Simultaneous Localisation and Mapping with a Single Camera," Proceeding of Ninth IEEE International Conference on Computer Vision, Nice, France, October 13-16 2003.
  23. Mahon, I., Williams, S. B., Pizarro, O. and Johnson-Roberson, M., "Efficient View-based SLAM Using Visual Loop Closures," IEEE Transactions on Robotics, Vol. 24, No. 5, 2008, pp. 1002-1014. https://doi.org/10.1109/TRO.2008.2004888
  24. Engel, J., Schöps, T. and Cremers, D. "LSD-SLAM: Large-scale Direct Monocular SLAM," Proceeding of European Conference on Computer Vision, Zurich, Switzerland, September 6-12 2014, pp. 834-849.
  25. Harmat, A., Trentini, M. and Sharf, I., "Multi-camera Tracking and Mapping for Unmanned Aerial Vehicles in Unstructured Environments," Journal of Intelligent and Robotic Systems, Vol. 78, No. 2, 2015, pp. 291-317. https://doi.org/10.1007/s10846-014-0085-y
  26. Forster, C., Faessler, M., Fontana, F., Werlberger, M. and Scaramuzza, D., "Continuous on-board monocular-vision-based elevation mapping applied to autonomous landing of micro aerial vehicles," Proceeding of IEEE International Conference on Robotics and Automation (ICRA), Seattle, USA, May 26-30 2015.
  27. Ranftl, R., Vineet, V., Chen, Q. and Koltun, V., "Dense Monocular Depth Estimation in Complex Dynamic Scenes," Proceeding of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, USA, June 27-30 2016.
  28. Habib, A., Asmamaw, A., Kelley, D. and May, M., "Linear feature in photogrammetry," Geodetic science and surveying, 2000, pp. 21-36.
  29. SimGEN Software User Manual, Spirent Communication plc, November 2015.