# L5 IN: Overview of an Indoor Navigation Pilot Project
## 2 L5 IN Project Overview
### Position Estimation
The pitch and roll are reliably calculatable based on the gravity estimation from accelerometer measurement [35]. However, a calibrated geomagnetic sensor value needs to be followed by a local magnetic map. Such a radio map or a magnetic distortion map relies heavily on a labelled dataset [36]. The next challenge addresses the different approaches of sensor tracking and pedestrian positioning. Research on orientation tracking in the context of indoor positioning tries to assess the heading of the device rather than the heading of the pedestrian. They therefore assume that the position of the mobile device is fixed and known or they neglect the misalignment between the smartphone heading and the user's walking direction as an open problem [37]. However, there have been some attempts to calculate the heading independent of orientation, based on acceleration values and the principal component analysis (PCA) calculation [38] or similar approaches, such as frequency domain analysis, but there is potential for improvement to achieve the desired accuracy [39]. To overcome the abovementioned challenges, map support is not enough. Therefore, 5G positioning, which is an infrastructure-based solution and provides absolute position information, will be used for the L5 IN project. The potential of 5G technology is seen as the base requirement. Dense 5G networks with a range of a few meters to tens of metres are envisaged. For instance, one can assume several access nodes per room in indoor environments and one access node on each lamp in outdoor areas [40]. In view of the popularity of smartphones for positioning, 5G-based methods are a perfect complement. It has been shown that an accuracy of 1 m and better is achieved in 70% of cases when different 5G positioning techniques are used [40]. Proximity, time of arrival (ToA), and direction of arrival (DoA), in combination with Kalman filtering, are common in the 5G positioning domain. In the proximity method, the position of the mobile terminal is calculated relative to the antenna node positions, for which the cell ID (CID) or the received signal strength can be used. For the ToA method, the propagation delay from a mobile terminal to an antenna node is measured. The distance is the propagation delay multiplied by the propagation speed of the signal (speed of light). The position of a mobile terminal can then be calculated using trilateration from the distances to several antenna nodes. For the DoA, the direction of the signal propagation from a mobile terminal to a referenced antenna node is measured using antenna arrays. To determine the angle, the difference of the time of arrival (TDoA) at each element of the antenna array is measured. These methods will be discussed and developed in future works. In summary, sensor-based positioning methods need to overcome the problem of inertial sensor drift with additional support, such as maps and accurate absolute positions, to keep error accumulation at bay. Regarding the process of the L5 IN project, 5G constraints can not only determine the initial position and orientation of the device, but can also provide solutions about the misalignment between the user and the device. Step detection and heading estimation methods can be accurately calibrated using 5G signals. The 5G runtime data and their related methods can be used in order to reach the required accuracy and frequency in a positioning task.