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Enhancing Location Estimation and Reducing Computation using Adaptive Zone Based K-NNSS Algorithm
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  • Enhancing Location Estimation and Reducing Computation using Adaptive Zone Based K-NNSS Algorithm
  • Enhancing Location Estimation and Reducing Computation using Adaptive Zone Based K-NNSS Algorithm
저자명
Song. Sung-Hak,Lee. Chang-Hoon,Park. Ju-Hyun,Koo. Kyo-Jun,Kim. Jong-Kook,Park. Jong-Sun
간행물명
KSII Transactions on internet and information systems : TIIS
권/호정보
2009년|3권 1호|pp.119-133 (15 pages)
발행정보
한국인터넷정보학회
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정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

The purpose of this research is to accurately estimate the location of a device using the received signal strength indicator (RSSI) of IEEE 802.11 WLAN for location tracking in indoor environments. For the location estimation method, we adopted the calibration model. By applying the Adaptive Zone Based K-NNSS (AZ-NNSS) algorithm, which considers the velocity of devices, this paper presents a 9% improvement of accuracy compared to the existing K-NNSS-based research, with 37% of the K-NNSS computation load. The accuracy is further enhanced by using a Kalman filter; the improvement was about 24%. This research also shows the level of accuracy that can be achieved by replacing a subset of the calibration data with values computed by a numerical equation, and suggests a reasonable number of calibration points. In addition, we use both the mean error distance (MED) and hit ratio to evaluate the accuracy of location estimation, while avoiding a biased comparison.