Exploiting User Movement Direction and Hidden Access Point for Smartphone Localization

Abstract

In this paper, we propose a global positioning system-less localization method, called Hidden Access Point Estimation-based Localization (HAPEL) to pinpoint user's current position in an underground or indoor environment, especially where access points (APs) are placed scarcely in that two or less Wi-Fi APs are within the scanning range. Conceptually, HAPEL enhances the weighted centroid localization (WCL) by exploiting hidden APs and estimating the direction of user movement. The movement direction can be estimated with digital compass, accelerometer and gyroscope, all of which are usually installed on smartphones, and the estimation result is used to choose which hidden APs participate in the WCL. We have conducted a performance evaluation study on HAPEL in comparison with WCL and fingerprint methods in an empirical test-bed. The results indicate that HAPEL improves the accuracy of the WCL significantly.