Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Indoor Positioning Algorithm Combining Bluetooth Low Energy Plate with Pedestrian Dead Reckoning

BLE Beacon Plate 기법과 Pedestrian Dead Reckoning을 융합한 실내 측위 알고리즘

  • Lee, Ji-Na (Dept. of IT Policy and Management, Soongsil University) ;
  • Kang, Hee-Yong (Dept. of IT Policy and Management, Soongsil University) ;
  • Shin, Yongtae (Dept. of IT Policy and Management, Soongsil University) ;
  • Kim, Jong-Bae (Graduate School of Software, Soongsil University)
  • Received : 2017.11.22
  • Accepted : 2017.12.02
  • Published : 2018.02.28
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Abstract

As the demand for indoor location recognition system has been rapidly increased in accordance with the increasing use of smart devices and the increasing use of augmented reality, indoor positioning systems(IPS) using BLE (Bluetooth Lower Energy) beacons and UWB (Ultra Wide Band) have been developed. In this paper, a positioning plate is generated by using trilateration technique based on BLE Beacon and using RSSI (Received Signal Strength Indicator). The resultant value is used to calculate the PDR-based coordinates using the positioning element of the Inertial Measurement Unit sensor, We propose a precise indoor positioning algorithm that combines RSSI and PDR technique. Based on the plate algorithm proposed in this paper, the experiment have done at large scale indoor sports arena and airport, and the results were successfully verified by 65% accuracy improvement with average 2.2m error.

스마트 기기의 생활화와 증강현실 활용 증가로 실내 위치 인식 시스템의 수요가 급증함에 따라, BLE(Bluetooth Lower Energy) 비콘 그리고 UWB(Ultra Wide Band) 등을 이용한 실내 측위 시스템이 개발되고 있다. 본 논문에서는 BLE Beacon을 기반으로 RSSI(Received Signal Strength Indicator)를 이용한 삼변측량(Trilateration) 기법을 사용하여 측위 플레이트(Plate)를 생성한다. 이에 IMU(Inertial Measurement Unit) 센서의 방향, 속도, 이동거리 등의 데이터를 이용하여 PDR(Pedestrian Dead Reckoning) 측위 좌표를 산출하여 정확도를 보정한다. 또, BLE 비콘(Beacon)의 RSSI를 적용한 플레이트(Plate) 기법과 PDR 기법이 융합된 정밀 실내 측위 알고리즘을 제안한다. 본 논문에서 제시한 알고리즘을 실제 대형 실내 경기장과 공항에 BLE 비콘을 설치, 실험하여 평균 2.2m 의 오차로 65%의 정확도가 개선됨을 검증하였다.

Keywords

References

  1. R. Faragher and R. Harle, Innovation : Getting Closer to Everywhere, GPS World, Oct. 2013. [Internet]. Available: http://gpsworld.com/innovation-getting-closer-to-everywhere-accurately-tracking-smartphones-indoors/.
  2. S. J. Jeong, J. H. Yim, "Implementation of the Passenger Positioning Systems using Beacon," Journal of the Korea Institute of Information and Communication Engineering, vol.20, no.1, pp.153-160, Jan. 2016. https://doi.org/10.6109/jkiice.2016.20.1.153
  3. Y. I. Kim, M. J. Kim, H. C. Kim, "Implementation of total management system for exhibitions and Convention using beacon," Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, vol.6, no.2, pp.35-44, Feb. 2016.
  4. X. Li, J. Wang, C. Liu, "A Bluetooth/PDR integration algorithm for an indoor positioning system", Sensors, vol. 15, no. 10, pp. 24862-24885, Sep. 2015. https://doi.org/10.3390/s151024862
  5. L. Parv, How To Choose the Right Indoor Positioning System? [Internet]. Available: https://www.eliko.ee/chooseright-indoor-positioning-system/
  6. K. Kaemarungsi, and P. Krishnamurthy, "Modeling of Indoor Positioning Systems Based on Location Fingerprinting," in Proc. Institute of Electrical and Electronics Engineers International Conference on Computer Communications, pp. 1012-1022, May 2004.
  7. Z. Li, C. Liu, J. Gao and X. Li, "An Improved WiFi/PDR Integrated System Using an Adaptive and Robust Filter for Indoor Localization," International Society for Photogrammetry and Remote Sensing International Journal of Geo-Information, vol. 5, no. 12, pp. 224-239, Nov. 2016.
  8. J. Huh, C. Lee, and J. Kim, "A study of beacon delivery characteristics in BLE based fingerprinting indoor positioning system," in proc. Korean Institute of Information Scientists and Engineers, vol.2015. no.6, pp 1612-1614, 2015.
  9. A. C. Salas, "Indoor Positioning System based on Blutetooth low Energy," Bachelor thesis, Universitat Politecnia de Catalunia Barcelonatech, Barcelona, Jun. 2014.
  10. M. Rainer, Indoor Positioning Technologies, Ph.D. Dissertation, Eidgenossische Technische Hochschule Zurich, Zurich, Switzerland, 2012.
  11. Y. Zhou, X. Zheng, H. Xiong and R. Chen, "Robust Indoor Mobile Localization with a Semantic Augmented Route Network Graph," International Society for Photogrammetry and Remote Sensing International Journal of Geo-Information, vol. 6, no. 7, pp. 221-246, Jul. 2017.
  12. T. Heinecke and M. Wolfe, "The Role of Bluetooth Low Energy for Indoor Positioning Application," [Internet]. Available: https://www.authorea.com/users/109065/articles/138441-the-role-of-bluetooth-low-energy-for-indoor-positioning-applications/_show_article#.
  13. L. Fang, P. J. Antsaklis, L. A. Montestruque, M. B. McMickell, M. Lemmon, Y. Sun, H. Fang, I. Koutroulis, M. Haenggi, M. Xie, and X. Xie, "Design of a Wireless Assisted Pedestrian Dead Reckoning System-The NavMote Experience," IEEE Transactions on Instrumentation and Measurement, vol. 54, no. 6, pp. 2342-2358, Nov. 2005. https://doi.org/10.1109/TIM.2005.858557

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