Deployment of RSS-Based Indoor Positioning Systems |
| |
Authors: | Christian Esposito Massimo Ficco |
| |
Affiliation: | 1.Dipartimento di Informatica e Sistemistica,Universitá di Napoli Federico II,Napoli,Italy;2.Laboratorio ITEM ‘C. Savy’, Consorzio Interuniversitario Nazionale per l’Informatica,Napoli,Italy |
| |
Abstract: | Location estimation based on Received Signal Strength (RSS) is the prevalent method in indoor positioning. For such positioning
systems, a massive collection of training samples is needed for their calibration. The accuracy of these methods is directly
related to the placement of the reference points and the radio map used to compute the device location. Traditionally, deploying
the reference points and building the radio map require human intervention and are extremely time-consuming. In this paper
we present an approach to reduce the manual calibration efforts needed to deploy an RSS-based localization system, both when
using only one RF technology or when using a combination of RF technologies. It is an automatic approach both to build a radio
map in a given workspace by means of a signal propagation model, and to assess the system calibration that best fits the required
accuracy by using a multi-objective genetic algorithm. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|