| Summary: | 碩士 === 國立政治大學 === 資訊科學學系 === 94 === Context-aware applications become more and more popular in today’s life. Location-aware information derives a lot of research issues. This thesis presents a precise indoor RF-based WLAN (IEEE 802.11) locating system named Precise Indoor Locating System (PILS). Most proposed location systems acquire well location estimation results but consume high level of manual efforts to collect huge amount of signal data. As a consequence, the system becomes impractical and manpower-wasted. In this thesis, we aim to reduce the manual efforts in constructing radio map and maintain high accuracy in our system. We propose the models for data calibration, interpolating, and location estimation in PILS. In the data calibration and location estimation models, we consider the autocorrelation of signal samples to enhance accuracy. Large scale and small scale fading are involved in the wireless channel propagation model. We also propose a learning model to adjust radio map for improving the accuracy down caused by calibrated data reduction.
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