A Low-Infrastructure Approach to Indoor Localization and Tracking using Lighting Information

Abstract

Low-infrastructure techniques for indoor localization attempt to provide indoor positioning information for users, without requiring the installation of specialized transmitting or receiving hardware. Such an approach should encourage further adoption of indoor positioning systems by reducing the installation burden on individual building owners. If fully adopted, indoor positioning could prove to be a valuable addition to the existing outdoor localization system based on GPS. In this work, a particle filter is used to combine motion and light data in order to provide positioning information for a user in an indoor environment. A simple lighting model is used to predict light measurements, while an orientation tracking algorithm provides information about user motion. The system is shown to work with the existing lighting infrastructure of a building, though the addition of visible light communication (VLC) enabled light fixtures is shown to further improve performance. An experimental demonstration of the proposed system is provided, which indicates that tracking accuracy on the order of ten’s of centimetres is possible with very low infrastructure requirements.