Concept for building a smartphone based indoor localization system

Global Navigation Satellite Systems (GNSS)-based navigation with smartphones is very popular. But in areas where no GNSS signal is found navigation could be useful. Examples are navigation in shopping malls, in big offices, in train stations or museums. The goal is to estimate the position in GNSS shaded areas to make navigation possible. The MEMS sensors (Micro Electro Mechanical System) installed in current smartphones, such as accelerometer, gyroscope, magnetic field sensor and barometer allow now navigation also in GNSS shadowed areas. Due to the low quality of these sensors, however, support of the position estimate is needed. In this work, a concept is presented for the construction of an indoor navigation system based on low-cost sensors of smartphones. The position estimate from the available sensor data forms the basis of the position determination. So position estimation is always possible independent of location. First results with Kalman filter and particle filter are shown. The presented concept serves as a basis for the construction of a smartphone-based navigation solution for indoor use. Therefore the available MEMS sensors should be used as a position estimator and a wide variety of supporting information can be processed. A first approach for implementation on a smartphone is shown as an example.