Towards Sub-Meter Level UWB Indoor Localization Using Body Wearable Sensors

Abstract

Thanks to its ability to provide sub-meter level positioning accuracy, Ultrawideband (UWB) has found wide use in several wireless body area network (WBAN) applications such as ambient assisted living, remote patient management and preventive care, among others. In spite of the attractiveness of UWB, it is not possible to achieve this level of accuracy when the human body obstructs the wireless channel, leading to a bias in the Time of Flight (TOF) measurements, and hence a detection of position errors of several meters. In this paper, a study of how a sub-meter level of accuracy can be achieved after compensating for body shadowing is presented. Using a Particle Filter (PF), we apply UWB ranging error models that take into consideration the body shadowing effect and evaluate them through simulations and extensive measurements. The results show a significant reduction in the median position error of up to 75 % and 82 % for simulations and experiments, respectively, leading to the achievement of a sub-meter level of localization accuracy. INDEX TERMS Body wearable sensors, Human body shadowing, Localization, Ranging, Ultrawideband, Time of Flight, Particle Filter I. INTRODUCTION With rapid developments of computer and miniaturization technologies, wearable sensors are becoming an important part of our daily lives. With a market expected to grow to $ 70 billion in 2025 [1], wearables are widely used in several applications such as in sport science, rehabilitation, medical monitoring, surveillance, among others [2]-[4]. Therefore, they can be attached to shoes, eyeglasses, earrings, clothing, gloves and watches, etc of the user of the wearable. Collecting precise user localization information is one of the salient capabilities of wearables [5]. In fact, according to [6], a sub-meter level of localization accuracy is envisaged for several wireless body area networks (WBAN). Currently, Global Navigation Satellite System (GNSS) is the most widely spread localization technology in outdoor environments.

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