Journal of Advanced Navigation Technology (한국항행학회논문지)

The Korean Navigation Institute (한국항행학회)
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Wi-Fi Based Indoor Positioning System Using Hybrid Algorithm

하이브리드 알고리즘을 이용한 Wi-Fi 기반의 실내 측위 시스템

  • Shin, Geon-Sik (Department of Computer Science & Engineering, Seoul National University of Science and Technology) ;
  • Shin, Yong-Hyeon (Department of Computer Science & Engineering, Seoul National University of Science and Technology)
  • 신건식 (서울과학기술대학교 컴퓨터공학과) ;
  • 신용현 (서울과학기술대학교 컴퓨터공학과)
  • Received : 2015.11.20
  • Accepted : 2015.12.22
  • Published : 2015.12.30
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Abstract

GPS is the representative positioning technology for providing the location information. This technique has the disadvantage that does not operate in the shadow areas, such as urban or dense forest and the interior. This paper proposes a hybrid indoor positioning algorithm, which estimates a more accurate location of the terminal using strength of the Wi-Fi signal from the indoor AP. To determine the location of the user, we establish the most appropriate path loss model for the measurement environment. by using the RSSI value measured in a variety of environment such as building structure, person, distance, etc. The path loss exponent obtained by the path loss model is changed according to the environment. REKF, PF estimate the position of the terminal by using measured value from the AP with path loss exponent. For more accurate position estimation, we select positioning system by the value of threshold measured by experiments rather than a single positioning system. Experimental results using the proposed hybrid algorithm show that the performance is improved by about 17% than the conventional single positioning method.

위치 정보를 제공하는 대표적인 측위 기술은 GPS다. 이 기술은 밀도가 높은 도심이나 숲, 그리고 실내와 같은 음영지역에서는 동작하지 않는 단점이 있다. 본 논문은 실내의 AP로 부터의 Wi-Fi 신호의 세기를 이용하여 보다 정확한 단말의 위치를 추정하게 해주는 실내 측위 하이브리드 알고리즘을 제안한다. 사용자의 위치를 결정하기 위해 건물 구조, 사람, 거리 등 다양한 환경에서 측정한 RSSI (received signal strength indicator) 값을 이용하여 측정 환경에 맞는 가장 적절한 경로손실모델을 수립한다. 이러한 경로 손실 모델에서 구해진 경로손실지수를 환경에 따라 변화시켜, AP로 부터 얻은 측정값을 이용하여 REKF (robust extended kalman filter)와 PF (particle filter) 알고리즘을 사용하여 단말기의 위치를 추정하게 된다. 보다 더 정확한 위치 추정을 위해 하나의 측위 방식만을 사용하지 않고, 실험을 통하여 구해진 임계값에 따라 어떠한 측위방식을 사용할 것인지를 결정한다. 제안한 하이브리드 알고리즘을 이용하여 실험한 결과 기존의 단일 측위 방식 보다 평균 17% 성능이 향상 되는 것을 볼 수 있었다.

Keywords

References

  1. V. Patmanathan, Area localization using WLAN, Electrical Engineering, Master of Science Thesis Stockholm, Sweden, SE, 2006.
  2. J. Hightower and G. Borriello, “Location system for ubiquitous computing,” IEEE Computer Society, Vol. 34, No. 8, pp. 57-66, Aug. 2001.
  3. A. Ward, A. Jones and A. Hopper, "A new location technique for the active office," IEEE Personal Communication Vol. 4, No. 5, pp. 42-47, Oct. 1997. https://doi.org/10.1109/98.626982
  4. M. Brunato and K. Csaba, "Transparent location fingerprinting for wireless services," in Proceedings of Med-Hoc-Net, Mediterranean Workshop on Ad-hoc Networks, Baia Chia: Cagliari, pp. 2-3, 2002.
  5. N. Patwari, J. Ash, N. Joshua, S. Kyperountas, A. O. Hero, R. L. Moses and N. S. Correal, "Locating the nodes: cooperative localization in wireless sensor networks," IEEE Signal Processing Magazine, Vol.22, No.4, pp. 54-69, Jul. 2005. https://doi.org/10.1109/MSP.2005.1458287
  6. F. Gustafsson and F. Gunnarsson, "Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements," IEEE Signal Processing Magazine, Vol.22, No.4, pp. 41-53, Jul. 2005. https://doi.org/10.1109/MSP.2005.1458284
  7. P. Bahl and V. N. Padmanabhan, "Radar: an in-building rf-based user location and tracking system," in Proceedings of Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, Tel Aviv: Israel, Vol. 2, pp. 775-784, 2000.
  8. T. S. Kim, Wlan-based Indoor Localization with APs as reference points, Ph.D. dissertation, University of Seoul, Korea, 2010.
  9. Y. Wang and X. Jia, "An indoors wireless positioning system based on wireless local area network infrastructure," in The 6th International Symposium on Satellite Navigation Technology Including Mobile Positioning & Location Service, Melbourne: Australia, pp. 5-11, Jul, 2003.
  10. J. Ting, A. D'Souza and S. Schaal, "Automatic outlier detection: a bayesian approach," in 2007 IEEE International Conference on Robotics and Automation, Angelicum University Roma: Italy, Vol.10, No.14, pp.2489-2494, Apr. 2007.
  11. B. Le, K. Ahmed and H. Tsuji, "Mobile location estimator with NLOS mitigation using Kalman filtering," IEEE Wireless Communications and Networking, Vol.3, pp.1969-1973, 2003.