Our paper on Robust indoor localization across smartphone models with ellipsoid features from multiple RSSIs has been published in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT).
We propose a novel feature representation based on multiple RSSIs for compensating performance degradation
against smartphone models changes.
In contrast to the previous feature representation based on a single RSSI, our new feature representation, which we call Ellipsoid features, employs tuples of pair of RSSIs to eliminate device dependence in the path loss model for wave propagation.
Experimental result using smartphone devices including Android Nexus5, Nexus5X, Nexus6P, and Xperia X Performance shows that our approach achieves superior performance over the state-of-the-art indoor localization models as well as robust performance against device changes.
The paper will be publicly available, i.e. open access in the following url, please check our paper.
Masato Sugasaki, Masamichi Shimosaka
Robust indoor localization across smartphone models with ellipsoid features from multiple RSSIs
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) Volume 1, Issue 2, pp. ???-???, 2017