A novel RSSI based approach for human indoor localization: The Fuzzy Discrete Multilateration

Abstract

In this paper a new algorithm for indoor localization, namely Fuzzy Discrete Multilateration (FDM), is proposed. As the name suggests, it elaborates data from any number of transmitters (anchor nodes), and returns the estimated position of an unknown receiver. Furthermore, two cascade fuzzy inference systems are employed to evaluate the reliability of the data gathered from each beacon. The algorithm has been tested in different real world environments, where the anchor nodes are smart objects and the unknown node is any smart object held by the user to be localized. The performances of our algorithm has been compared with those of three well known localization algorithms (with a beacon density ranging from 0.03 to 0.1 beacon/m2) and results are shown.