| Summary: | 碩士 === 國立政治大學 === 資訊科學學系 === 96 === Following the raise of Wireless LAN networks, there are a lot of relative research issues in today’s life. Tracking and locating mobile users in RF-based WLAN (IEEE 802.11) is a very important issue in location-based applications area. The error distances of indoor WLAN locating was decreased to approximately 1.5 meter in recent years. However, the improvement in accuracy was limited due to the nature of radio propagation. Many researches which contain precise accuracy were based on an impractical effort of collecting too much signal data which we usually called “calibration” in this area. So this thesis focuses on how to reduce the calibration efforts without losing too much accuracy. Confirming the allocation of access points is another kind of calibration effort we concerned.
As a consequence, we proposed a new locating system: first we calibrated few points and utilized inferring AP’s position and interpolation to complete radio map. During location estimation phase, radio map could be updated dynamically using learning mechanism modeled by HMM and other algorithms. In the experimental results, we proved our system maintained a comparable accuracy under reducing much calibration effort than other two locating systems. Besides, we analyzed the performance of our system with elder radio map and in two different experimental environments.
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