Fingerprinting-Based Indoor Positioning Systems

This book presents a novel approach for indoor localization that is based on the well know fingerprinting. This method is a two steps process. In the first step, also called training, a set of measurements (typically RSSI) are collected from reference points in the localization area and stored into a database (or radio map). In the second step, the online measurements are compared to the stored radio map, and the position is estimated through pattern matching techniques. The main contribution proposed, consist in reducing the quantization bits of the measurements (RSSI) up to 1 bit, therefore we get a radio map that is binary. We exploited the similarity between binary coding and localization by introducing the concept of Hamming distance to evaluate the training set and to propose a design strategy for an easy implementation of IPS.