Pedestrian Inertial Navigation

Abstract

Even though technology-aided pedestrian navigation is an extensively studied research topic, a commercial system is not yet available. However, the ability to locate a person in “any” environment is a key feature in several applications. In outdoor environments, the position can be obtained through satellite-based systems or by triangulating radio signals (e.g., from cellular base stations). All these approaches rely on the use of transmitting devices placed in known positions in order to determine by triangulation, the position of the user’s receiving device. However, the costs and complexity, associated with a pre-deployed infrastructure and its maintenance, together with an often limited position accuracy, represent the mail limitation to an extensive adoption of these technologies, in particular in indoor environments. Inertial navigation-based solutions can overcome these limitations because of their independence from external infrastructures. Inertial Navigation Systems (INSs) exploit data collected through Inertial Measurement Units (IMUs) to continuously estimate the position, orientation, and velocity of a moving user. Leveraging the sensor’s cost reductions, the massive diffusion, in commercial devices, of cheap IMUs can be exploited to perform pedestrian inertial navigation. In this dissertation, an extensive overview over the possible approaches already existing in the literature is first provided (Chapter 1). In particular, this work mainly focuses on purely inertial navigation systems. A preliminary analysis of the algorithms able to relate inertial signals to the body displacement is given. Then, two innovative algorithms for pedestrian navigation are proposed (Chapter 2). These solutions exploit different body dynamics because of the different sensor on-body placement. After that, a thorough analysis relative to the impact of the sensors’ placement over the human body is provided. Different approaches are studied, and, then, the fusion of the signals collected through different IMUs is proposed in order to increase the accuracy with respect to the systems based on single sensor (Chapter 3 and Chapter 4). The evaluation of the possible approaches to inertial navigation has also led to the use of hand-held commercial devices (Chapter 5). In particular, an innovative algorithm to perform inertial navigation based on the data collected through the IMU embedded in a smartphone is proposed. The considered algorithms are validated through an extensive experimental campaign with multiple smartphones. The obtained results show the feasibility of commercial pedestrian INSs, highlighting their strengths and weaknesses.