Experimental Analysis of Indoor Positioning System Based on Ultra-Wideband Measurements

Abstract: Localization is one of the most interesting research areas in wireless networks. It is mostly used for tracking and monitoring applications such as traffic monitoring, search and rescue, navigation and so on. A good quality system can be defined from its accuracy when operating in severe interference environments that contaminate the signals and therefore reduce the system performance. The main issue for localization is channel propagation, e.g., line of sight or non-line of sight channel which should be studied in order to improve the system efficiency.    In order to perform a localization, most algorithms use two steps: ranging and positioning. For ranging, the two popular techniques that are widely used for distance measurement are received signal strength (RSS) and time of arrival (TOA). RSS ranging technique uses the power of the received signals to identify the distance between a transmitter and a receiver. TOA ranging technique uses time of the signal traveling between a transmitter and a receiver to identify the distance, thus it requires synchronization. The measurements are processed by using a localization algorithm afterwards. However, these techniques suffer from multipath fading and other errors, so there always exists error in the estimated position.    In this thesis, TOA ranging technique is used for different estimation methods. Simulation results are performed using MATLAB, while the real results are obtained from Pozyx indoor positioning platform. Several estimation algorithms comprising of maximum likelihood (ML), linearized least square (LLS), weighted centroid (WC), and fingerprinting (FP) are studied in detail. The testing area is indoor environment which is suitable for LOS, NLOS and combined situations. The measured data is then used for ranging and localization. We concentrate on comparing and discussing these results in this thesis.