Interpolation database construction for indoor WLAN localization via breakpoint propagation modeling

Abstract

Among different types of Wireless Local Area Network (WLAN) positioning systems, fingerprinting-based localization exhibits good accuracy performance, and thus becomes increasingly popular. Fingerprinting-based localization needs extensive calibration effort to construct a Received Signal Strength (RSS) fingerprint database, which hinders the large development of WLAN localization. In this paper, to reconstruct the raw sparse fingerprinting database and reduce manual effort, we propose a novel integrated Propagation Model-based Breakpoint Model Interpolation (PMBMI) and Multidimensional Linear Interpolation (MLI). We carry out extensive experiments in a ground-truth indoor environment to examine the localization accuracy of our proposed approach. Experimental results show that our proposed approach can be applied to reduce the labor cost in off-line phase, as well as guaranteeing high-enough accuracy performance.