期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2016
卷号：2016
DOI：10.1155/2016/1289013
出版社：Hindawi Publishing Corporation
摘要：With the rapid development of WLAN infrastructure, fingerprint-based positioning using signal strength has become a promising localization solution in indoor space. Commonly fingerprint-based positioning methods face two challenges in large indoor space, one is floor recognition in large building with multifloor, and the other is signal strength variance due to heterogeneous devices and environmental factors. In this paper, we propose a novel two-stage positioning approach to address these challenges of fingerprint-based positioning methods in large indoor space. Firstly, we design a floor-level recognition feature based on WiFi access points and the RSS values to recognize floor. For solving the signal strength variance problem, we propose a new metric to capture the similarity of location fingerprints probability distribution using KL Divergence. To demonstrate the utility of our approach, we have performed comprehensive experiments in a large indoor building.
