Cortina: Collaborative context-aware indoor positioning employing RSS and RToF techniques

Abstract

Cortina is an energy-efficient indoor localization system, which leverages a wireless sensor network to support navigation and tracking applications. To improve the localization performance, we develop a hybrid ranging system, which incorporate both RSS and RToF-based techniques. To overcome effects from indoor multipath, we design and implement algorithms to take into account various contextual information. We evaluated the system over a 2000m2 area instrumented with twenty-six fixed nodes. Evaluation results show the system achieved 2.5m accuracy in a pedestrian tracking application.