Indoor localization on mobile phone platforms using embedded inertial sensors

Abstract

Indoor localization techniques are commonly based on measuring the Wi-Fi received signal strength (RSS) and the method of "fingerprinting". The accuracy depends on density of recorded fingerprints in the radiomap (RM) database. Building and updating RM is expensive and labor-intensive. Taking advantage of ubiquity of smartphones with embedded inertial sensors yields an economic and easy-to-deploy indoor localization system. In this work, the accelerometer and digital compass are used to recognize the user's dynamic activities and walking directions. And the particle filter integrates the building map constraints and inertial measurements to estimate user's location. On this basis, an indoor localization system with no dense wireless site survey requirements is proposed and evaluated.