Dead Reckoning in Structured Environments for Human Indoor Navigation

Provision for unrestricted movement by everybody, including disabled people, is among the basic aims of a Smart City. In this paper, we deal with human indoor navigation based on inertial sensors that are commonly found in devices, such as smartphones. The approach has gathered broad interest within the scientific community, since it does not require installation of external devices and allows the use of a smartphone both as measurement platform and user interface. Thus, it can be seen as an inclusive low-cost, low-energy human navigation aid. We focus this paper on the implementation of algorithms for estimating and tracking the heading direction of a user walking within a structured environment, e.g., a building. The main feature of the proposed method is that the estimation of direction is not referred to absolute headings based on the four cardinal directions, as usually done in the literature. To achieve sufficient reliability and, at the same time, preserve simplicity, our approach is based on detecting relative changes in the user direction with respect to a reference system obtained during an initial calibration phase. The fundamental direction, which exhibits the minimum distance with respect to the raw measured values, is then provided as output. Experimental results reported in this paper show that a user path can be traced with sufficient accuracy within four steps in the worst case.