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Indoor localization algorithm based on WLAN using modified database and selective operation

변형된 데이터베이스와 선택적 연산을 이용한 WLAN 실내위치인식 알고리즘

  • Seong, Ju-Hyeon (Department of Electrical and Electronics Engineering, Korea Maritime and Ocean University) ;
  • Park, Jong-Sung (ACofS C4I, R. O. K. Naval Headquarters) ;
  • Lee, Seung-Hee (Department of Internet Game, Deakyeung University) ;
  • Seo, Dong-Hoan (Division of Electrical and Electronics Engineering, Korea Maritime and Ocean University)
  • Received : 2013.09.23
  • Accepted : 2013.10.28
  • Published : 2013.11.30

Abstract

Recently, the Fingerprint, which is one of the methods of indoor localization using WLAN, has been many studied owing to robustness about ranging error by the diffraction and refraction of radio waves. However, in the signal gathering process and comparison operation for the measured signals with the database, this method requires time consumption and computational complexity. In order to compensate for these problems, this paper presents, based on proposed modified database, WLAN indoor localization algorithm using selective operation of collected signal in real time. The proposed algorithm reduces the configuration time and the size of the data in the database through linear interpolation and thresholding according to the signal strength, the localization accuracy, while reducing the computational complexity, is maintained through selective operation of the signals which are measured in real time. The experimental results show that the accuracy of localization is improved to 17.8% and the computational complexity reduced to 46% compared to conventional Fingerprint in the corridor by using proposed algorithm.

최근 WLAN을 이용한 실내 위치인식 방법 중 하나인 Fingerprint 기법은 신호의 반사 및 굴절에 의한 페이딩 현상에 강인하여 많이 연구되고 있다. 그러나 이 방법은 신호의 수집과 데이터베이스와 측정된 신호의 비교 연산의 과정에서 요구되는 시간과 연산량이 많다. 본 논문에서는 연산량을 줄이기 위하여 제안한 변형된 데이터베이스를 기반으로 실시간으로 수집되는 신호의 선택적 연산을 이용한 WLAN 실내 위치인식 알고리즘을 제안한다. 제안한 알고리즘은 신호의 세기에 따른 선형보간과 문턱치를 통하여 데이터베이스의 구성 시간 및 크기를 줄이고, 실시간으로 측정되는 신호의 선택적 연산을 통해 연산량은 감소시키면서 위치정확도를 유지하였다. 실험결과 제안한 알고리즘은 실내 복도 환경에서 기존의 Fingerprint 기법 대비 정확도를 17.8% 향상시켰으며 연산량은 평균 46% 감소되는 것을 확인하였다.

Keywords

References

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