실내 측위 결정을 위한 Fingerprinting Bayesian 알고리즘

Fingerprinting Bayesian Algorithm for Indoor Location Determination

  • 투고 : 2010.03.08
  • 심사 : 2010.06.09
  • 발행 : 2010.06.30

초록

무선 네트워크 기반 실내 측위는 측위를 위한 특수 장비를 필요로 하지 않고, Fingerprinting 방식은 무선 네트워크 기반 측위를 위한 기술 중에서 가장 정확도가 높기 때문에 무선 네트워크 fingerprinting 방식이 가장 적당한 실내 측위 방법이다. Fingerprinting 방식은 준비 단계와 실시간 측위 단계로 구성되고 정확한 위치 측정을 위해 보다 효율적이고 정확해야 한다. 본 논문에서는 Fingerprinting 방식에 대한 베이지안 알고리즘으로 강력한 통계적 학습 이론인 베이지안 학습을 결합한 퍼지 군집화를 이용하여 실내 측위를 결정하는 알고리즘을 제안하였다.

For the indoor positioning, wireless fingerprinting is most favorable because fingerprinting is most accurate among the technique for wireless network based indoor positioning which does not require any special equipments dedicated for positioning. The deployment of a fingerprinting method consists of off-line phase and on-line phase and more efficient and accurate methods have been studied. This paper proposes a bayesian algorithm for wireless fingerprinting and indoor location determination using fuzzy clustering with bayesian learning as a statistical learning theory.

키워드

참고문헌

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