Skip navigation

SSD: A robust RF location fingerprint addressing mobile devices' heterogeneity

SSD: A robust RF location fingerprint addressing mobile devices' heterogeneity

Hossain, A.K.M. Mahtab, Jin, Yunye, Soh, Wee-Seng and Van, Hien Nguyen (2011) SSD: A robust RF location fingerprint addressing mobile devices' heterogeneity. IEEE Transactions on Mobile Computing, 12 (1). pp. 65-77. ISSN 1536-1233 (doi:https://doi.org/10.1109/TMC.2011.243)

[img]
Preview
PDF (Author Accepted Manuscript)
16357 HOSSAIN_Robust_RF_Location_Fingerprint_2011.pdf - Accepted Version

Download (1MB) | Preview

Abstract

Fingerprint-based methods are widely adopted for indoor localization purpose because of their cost-effectiveness compared to other infrastructure-based positioning systems. However, the popular location fingerprint, Received Signal Strength (RSS), is observed to differ significantly across different devices' hardware even under the same wireless conditions. We derive analytically a robust location fingerprint definition, the Signal Strength Difference (SSD), and verify its performance experimentally using a number of different mobile devices with heterogeneous hardware. Our experiments have also considered both Wi-Fi and Bluetooth devices, as well as both Access-Point(AP)-based localization and Mobile-Node (MN)-assisted localization. We present the results of two well-known localization algorithms (K Nearest Neighbor and Bayesian Inference) when our proposed fingerprint is used, and demonstrate its robustness when the testing device differs from the training device. We also compare these SSD-based localization algorithms' performance against that of two other approaches in the literature that are designed to mitigate the effects of mobile node hardware variations, and show that SSD-based algorithms have better accuracy.

Item Type: Article
Uncontrolled Keywords: Heterogeneous devices; Location fingerprint; Signal strength difference (SSD); Wi-Fi; Bluetooth; Indoor localization; Positioning system
Faculty / School / Research Centre / Research Group: Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Faculty of Engineering & Science
Last Modified: 04 Mar 2022 13:08
URI: http://gala.gre.ac.uk/id/eprint/16357

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics