The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Indoor Localization Algorithm Using Smartphone Sensors and Probability of Normal Distribution in Wi-Fi Environment

Wi-Fi 환경에서 센서 및 정규분포 확률을 적용한 실내 위치추정 알고리즘

  • Received : 2015.07.17
  • Accepted : 2015.09.11
  • Published : 2015.09.30
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Abstract

In this paper, the localization algorithm for improving the accuracy of the positioning using the Wi-Fi fingerprint using the normal distribution probability and the built-in typed accelerometer sensor, the gyroscope sensor of smartphone in the indoor environment is proposed. The experiments for analyzing the performance of the proposed algorithm were carried out at the region of the horizontal and vertical 20m * 10m in the engineering school building of our university, and the performance of the proposed algorithm is compared with the fingerprint and the DR (dead reckoning) while user is moving according to the assigned region. As a result, the maximum error distance in the proposed algorithm was decreased to 2cm and 36cm compared with two algorithms, respectively. In addition to this, the maximum error distance was also less than compared with two algorithms as 16.64cm and 36.25cm, respectively. It can be seen that the fingerprint map searching time of the proposed algorithm was also reduced to 0.15 seconds compared with two algorithms.

본 논문에서는 실내 환경에서 정규분포 확률을 이용한 Wi-Fi 핑거프린트 방식과 스마트 폰에 내장된 가속도 센서 (accelerometer sensor), 자이로스코프 센서 (gyroscope sensor)를 이용하여 정확도를 향상시킨 위치추정 알고리즘을 제안하고, 실제 실험을 통하여 성능을 분석하였다. 제안한 알고리즘의 성능 실험은 본 대학교 공대 건물내의 가로 세로 20m * 10m의 공간에서 실시하였으며, 사용자가 각 구간을 이동 할 때 제안한 알고리즘의 위치추정 성능을 핑거프린트 (fingerprint) 방식과 추측항법 (dead reckoning)과 서로 비교하였다. 실험 결과, 제안한 알고리즘의 성능은 두 방식과 비교 했을 때, 최대 오차 거리는 각각 2cm, 36cm, 그리고 평균 오차 거리는 각각 16.64cm, 36.25cm 더 우수함을 확인하였다. 또한, 핑거프린트 맵 (map) 탐색 알고리즘의 성능도 맵 전체를 탐색하는 방식에 비해 약 0.15초 더 단축됨을 확인하였다.

Keywords

References

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