Indoor Localization Based on Radio Channel Parameters by a Wireless Sensor Network

Wireless Sensor Networks are nowadays becoming increasingly popular. Due to their low cost, ease of  deployment and application, they offer robust solutions in a variety of fields. In this context, localization is one of the most important functionalities that can be implemented. The analysis of existing antennas that could suit a light, small, and energy-efficient sensor and the analysis and design of localization algorithms have been studied in this work. Indoor localization in a smart home poses certain challenges in comparison with the existing and successfully implemented large scale outdoor localization systems, due to the shadow fading effects and the notable differences among the indoor environments. This work has focused on localization based on channel parameters estimation and received signal strength. This offers versatility, since no previous knowledge of the indoor environment is required, and cheap deployment. A review of existing methods in this area is given and two classical and robust approaches, least squares estimation and log-likelihood maximization are combined to obtain new algorithms that can statistically improve the performance in terms of bias and variance of the error. The results of this work can be applied to the development of cheap and robustly optimized algorithms. Furthermore, the analysis of the antennas for this context sets the needs that new lines of future investigation and development of sensor devices can address.