Temporal correlation of the RSS improves accuracy of fingerprinting localization

Abstract

Indoor localization based on RSS fingerprinting approach has been attracting many research efforts in the past decades. Recent study presents a fundamental limit of the approach: given requirement of estimation accuracy, reliability of the user's localization result can be derived. As highly accurate indoor localization is essential to enable many location based services, a natural question to ask is: can we further improve the accuracy of the localization scheme fundamentally? In this paper, we theoretically show that the temporal correlation of the RSS can improve accuracy of the RSS fingerprinting based indoor localization. In particular, we construct a theoretical framework to evaluate how the temporal correlation of the RSS can influence the reliability of location estimation, which is based on a newly proposed radio propagation model considering the time-varying property of signals from a given Wi-Fi AP. Such a theoretical framework is then applied to analyze localization in the one dimensional physical space, which reveals the fundamental reason why performance improvement of localization can be brought by temporal correlation of the RSS. We further extend our analysis to high-dimensional scenarios. Experimental results corroborate our theoretical analysis.