DOI QR코드

DOI QR Code

Pedestrian Navigation System in Mountainous non-GPS Environments

  • Lee, Sungnam (Department of Electronics and Communications Engineering, Korea Air Force Academy)
  • Received : 2021.01.31
  • Accepted : 2021.09.14
  • Published : 2021.09.30

Abstract

In military operations, an accurate localization system is required to navigate soldiers to their destinations, even in non-GPS environments. The global positioning system is a commonly used localization method, but it is difficult to maintain the robustness of GPS-based localization against jamming of signals. In addition, GPS-based localization cannot provide important terrain information such as obstacles. With the widespread use of embedded sensors, sensor-based pedestrian tracking schemes have become an attractive option. However, because of noisy sensor readings, pedestrian tracking systems using motion sensors have a major drawback in that errors in the estimated displacement accumulate over time. We present a group-based standalone system that creates terrain maps automatically while also locating soldiers in mountainous terrain. The system estimates landmarks using inertial sensors and utilizes split group information to improve the robustness of map construction. The evaluation shows that our system successfully corrected and combined the drift error of the system localization without infrastructure.

Keywords

References

  1. S. Lee, Y. Chon, and H. Cha, "Smartphone-based indoor pedestrian tracking using geo-magnetic observations," Mobile Information Systems, vol. 9, no. 2, pp. 123-137, 2013. DOI: 10.1155/2013/295838.
  2. Z. Wang, Y. Piao, and M. Jin, "Laser spot detection using robust dictionary construction and update," Journal of Information and Communication Convergence Engineering, vol. 13, no. 1, pp. 42-49 (2015). DOI: 10.6109/jicce.2015.13.1.042
  3. P. Robertson, M. Angermann, and B. Krach, "Simultaneous localization and mapping for pedestrians using only foot-mounted inertial sensors," in Proc. Ubicomp '09, New York, NY, pp. 93-96, 2009. DOI: 10.1145/1620545.1620560.
  4. S. Lee, S. Mengliev, Y. Chon, R. Ha, and H. Cha, "Autonomous construction of a mountain terrain map using low-cost sensors and group information," in Proceedings of the IEEE Military Communications Conference (MILCOM 2013), San Diego, CA, 2013. DOI: 10.1109/MILCOM.2013.64.
  5. S. Lee, H. Shin, and H. Cha, "A pedestrian tracking system using group mobility information," in Proc. MILCOM 2012, 2012. DOI: 10.1109/MILCOM.2012.6415710.
  6. A. LaMarca, Y. Chawathe, and S. Consolvo, "Place lab: Device positioning using radio beacons in the wild," Pervasive Computing, pp. 116-133, 2005. DOI: 10.1007/11428572_8.
  7. A. I. Moura, C. H. C. Ribeiro, and A. H. R. Costa, "WBLS: A signal presence-based wi-fi localisation system for mobile devices in smart environments," International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 13, no. 1, pp. 5-18, 2009. DOI: 10.3233/KES-2009-0169.
  8. P. Bahl and V. N. Padmanabhan, "RADAR: An in-building RF-based user location and tracking system," in Proc. 19th Annual Joint Conference of the IEEE Computer and Communications Societies. (INFOCOM), vol. 2, pp. 775-784, 2000. DOI: 10.1109/INFCOM.2000.832252.
  9. N. B. Priyantha, A. Chakraborty, and H. Balakrishnan, "The cricket location-support system," in Proc. 6th Annual International Conference on Mobile Computing and Networking (MobiCom), Boston, MA, pp. 32-43, 2000. DOI: 10.1145/345910.345917.
  10. R. Want, A. Hopper, V. Falcao, and J. Gibbons, "The active badge location system," ACM Transactions on Information Systems, vol. 10, no. 1, pp. 91-102, 1992. DOI: 10.1145/128756.128759.
  11. Y. Jin, M. Motani, W. S. Soh, and J. Zhang, "SparseTrack: Enhancing indoor pedestrian tracking with sparse infrastructure support," in Proc. IEEE INFOCOM, pp. 1-9, 2010. DOI: 10.1109/INFCOM.2010.5462157.
  12. H. Shin, Y. Chon, and H. Cha, "Unsupervised construction of indoor floor plan using smartphone," IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews (SMCC), vol. 42, no. 6, pp. 889-898, Nov. 2012. DOI: 10.1109/TSMCC.2011.2169403.
  13. H. Wang, S. Sen, A. Elgohary, M. Farid, M. Youssef, and R. R. Choudhury, "No need to war-drive: Unsupervised indoor localization," in Proc. 10th International Conference on Mobile Systems, Applications, and Services (MobiSys), Lake District, UK, pp. 197-210, 2012. DOI: 10.1145/2307636.2307655.
  14. I. Constandache, R. R. Choudhury, and I. Rhee, "Towards mobile phone localization without war-driving," in Proc. IEEE INFOCOM, pp. 1-9, 2010. DOI: 10.1109/INFCOM.2010.5462058.
  15. Y. Ohtaki, D. Hu, K. Hashimoto, and H. Inooka, "A method of personal positioning for indoor customer tracking utilizing wearable inertial sensors," International Journal of Applied Electromagnetics and Mechanics, vol. 36, no. 1-2, pp. 75-83, 2011. DOI: 10.1117/12.664238.
  16. I. Constandache, R. R. Choudhury, and I. Rhee, "CompAcc: Using mobile phone compasses and accelerometers for localization," in Proc. INFOCOM, San Diego, CA, 2010.
  17. Y. Jin, H. S. Toh, W. S. Soh, and W. C. Wong, "A robust deadreckoning pedestrian tracking system with low cost sensors," in Proc. IEEE International Conference on PerCom, pp. 222-230, 2011. DOI: 10.1109/PERCOM.2011.5767590.
  18. M. Hardegger, G. Troester, and D. Roggen, "Improved actionSLAM for long-term indoor tracking with wearable motion sensors," in Proc. 2013 International Symposium on Wearable Computers (ISWC '13), New York, NY, pp. 1-8, 2013. DOI: 10.1145/2493988.2494328.
  19. M. Figueiredo, A. D. Almeida, and B. Ribeiro, "Home electrical signal disaggregation for non-intrusive load monitoring (NILM) systems," Neurocomputing, vol. 96, pp. 66-73, 2012. DOI: 10.1016/j.neucom.2012.10.037.