# L5 IN: Overview of an Indoor Navigation Pilot Project
## 2 L5 IN Project Overview
### Position Estimation  
Micro-electro-mechanical systems (MEMS) are found in every smartphone. Reliable indoor positioning based on MEMS has been one of the goals of researchers in recent years. Among all of the available sensors in smartphones, inertial measurement units (IMUs) are those sensors that can be used at any time. Therefore, many positioning techniques rely on them as key sensors. Focusing only on the sensor-based methods with special attention on smartphones, it seems to provide a promising solution for people's everyday lives. However, positioning techniques are still mostly limited to sensor drifts, placements, and defined labeled data. Therefore, wide ranges of different sensor technologies have been used to overcome the challenges in developing an indoor positioning system. Generally, inertial sensors can be used to provide information about the orientation and position of any object that they are attached to. In 2010, smartphones with gyroscope sensors (such as the iPhone 4 [27]) were used for the first time after decades of studying the methods of the strapdown inertial navigation system (INS) [28]. Researchers were able to determine the 3D position, velocity, and attitude of sensors by integrating the raw data from the accelerometer and gyroscope. However, MEMS sensors are different from the expensive, heavy, and high precision IMUs used in ships, aircrafts, etc. Besides, in contrast to the traditional INS, mobile devices can be located in many different places, even without a unique pose in relation to the navigation body. Different scenarios of indoor positioning, such as on-shoe mounted and handheld techniques, began taking shape at this point in time. The basis of pedestrian dead reckoning (PDR) is a combination of a pedometer, a known or estimated stride length, and orientation. The activity detection methods for indoor localization purposes, such as in [29], and PDR methods have started to mature, hoping to address the problems with INS. Due to the popularity of smartphones, the previous experiences in both the INS and the PDR methods remained in the center of attention. Although there were different step counting algorithms in different time domains, frequency domains, and clustering moods, evaluation and comparison helped to clarify windowed peak detection as the optimal choice [30] for the L5 IN project, as it was shown to be work well in one of the most popular PDR benchmarks [31]. End-to-end systems are more complete systems that use different sensor fusion approaches, as well as external supports such as maps and absolute positioning techniques. They became even more interesting when passing doors and not walls, combined with topological approaches using particle filtering [32]. Due to the BIM generation process, geo-features and landmarks shape indoor positioning algorithms. For a robust real-time positioning solution, the challenges and open questions must be defined. The first challenge in research regarding pose tracking is how to determine the initial pose (position and orientation) of the device. This seems to be a very important problem, because if it is possible to calculate the initial position, then it should also be possible to determine the next points. However, in order to provide a high-quality position, absolute methods using WLAN, Bluetooth, or UWB are among those individual solutions that either push users to register into the desired network or create more sensitivity regarding small environmental or anchor changes, as can be seen in fingerprinting approaches [31; 32]. GPS initialization [33] is an accepted standard initialization method, but it obviously results in a strong limit for starting points. Manual user input is the only remaining way to start a navigation journey, maybe by using a QR code as another specialized solution [34]. While the real-time initial position needs to be solved by an absolute positioning technique,the initial orientation can be calculated differently for the pitch, roll and yaw.