A High-Precision Indoor Tracking System

Abstract

Location tracking is of paramount importance to many applications such as healthcare, retail and navigation. Outdoor tracking can be easily implemented using the Global Positioning System (GPS). However, indoor tracking has been a difficult problem to tackle because GPS requires the line of sight to the satellites and therefore it does not work well in indoor environments. In this thesis, a high-precision indoor tracking system is proposed to identify, locate and track a person in an indoor room at a low cost. The proposed tracking system consists of three components: StepscanTM tiles, RFID and Kalman-filter based prediction. The StepscanTM tiles can generate precise location information. However, using StepscanTM tiles only in an indoor tracking system is too expensive because the manufacturing cost of each StepscanTM tile is very high. In the proposed system, StepscanTM tiles are deployed to cover a part of the indoor floor while RFID provides a full coverage. The location information from StepscanTM tiles and RFID is then used as inputs for our innovative prediction algorithm based on the Kalman filter, which consequently generates high-precision tracking results. The performance of the proposed system is investigated through extensive simulations. Our simulation results indicate that the proposed system increases the capability to track and locate a person by at least 24% (more than 50% in some cases), with errors ranging from 2.5% to 15%. Furthermore, the proposed system helps to reduce the cost of indoor tracking significantly. In terms of the number of StepscanTM tiles deployed in the system, a reduction of 7 to 25 tiles can be achieved in the scenarios under investigation. In terms of monetary cost, $21,000 to $75,000 can be saved for an indoor tracking system considered in our research.