Reducing Calibration Effort for WLAN Location System using Segment Technique with Autocorrelation

Abstract

Context-aware applications become more and more popular in today's life. Location-aware information has derived a lot of research issues. This paper 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 effort to collect a huge amount of signal data. As a consequence, the system becomes impractical and manpower-wasted. In this paper, we aim to reduce the manual effort in constructing radio map and maintain high accuracy in our system. We propose models for data calibration, interpolating, and location estimation in PILS. In data calibration and location estimation models, we consider of autocorrelation of signal samples to enhance the accuracy. Wireless channel propagation model is also in our concern. Large scale and small scale fading are involved in the wireless channel propagation.