Abstract—Accurate indoor pedestrian tracking has wide applications in the healthcare, retail, and entertainment industries. However, existing approaches to indoor tracking have various limitations. For example, location-fingerprinting approaches are labor-intensive and vulnerable to environmental changes. Trilateration approaches require at least three Line-of-Sight (LoS) beacons to cover any point in the service area, which results in heavy infrastructure cost. Dead Reckoning (DR) approaches rely on knowledge of the initial user location and suffer from tracking error accumulation. Despite this, we adopt DR for location tracking because of the recent emergence of affordable hand-held devices equipped with low cost DR-enabling sensors. In this paper, we propose an indoor pedestrian tracking system which comprises a DR sub-system implemented on a mobile phone, and a ranging sub-system with a sparse infrastructure. A probabilistic fusion scheme is applied to bound the accumulated trac...