SparseLoc: Indoor Localization Using Sparse Representation.

	SparseLoc: Indoor Localization Using Sparse Representation.
	Chen, Kongyang ; Mi, Yue ; Shen, Yun ; Hong, Yan ; Chen, Ai ; Lu, Mingming
刊名	IEEE ACCESS
	2017
文献子类	期刊论文
英文摘要	With the popularity of smart mobile devices, "context-aware" applications have attracted intense interest, for which location is one of the most essential contexts. Compared with outdoor localization, indoor localization has received much more attention from both academia and industry these days. Given the widespread use of WiFi hotspots, the received signal strength (RSS) fingerprint-based indoorlocalization technique is considered as a promising and practical solution because of its relatively high accuracy and low infrastructure cost. Inspired by our observation that sparsity is inherent to the WiFi signal, we present a new RSS fingerprint-based indoor localization approach, called SparseLoc. Through sparse representation of the fingerprints, SparseLoc can estimate a smart mobile device's location with a small error most of the time. Although the correlation between neighboring fingerprints affects the localization accuracy, SparseLoc uses the similarity between principal components of fingerprints to alleviate this effect. Based on the empirical experiments, we demonstrate that SparseLocimproves the localization accuracy by over 25% compared with the existing WiFi signal-based localization methods.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12556]
专题	深圳先进技术研究院_数字所
作者单位	IEEE ACCESS
推荐引用方式 GB/T 7714	Chen, Kongyang , Mi, Yue , Shen, Yun ,et al. SparseLoc: Indoor Localization Using Sparse Representation.[J]. IEEE ACCESS,2017.
APA	Chen, Kongyang , Mi, Yue , Shen, Yun , Hong, Yan , Chen, Ai ,& Lu, Mingming.(2017).SparseLoc: Indoor Localization Using Sparse Representation..IEEE ACCESS.
MLA	Chen, Kongyang ,et al."SparseLoc: Indoor Localization Using Sparse Representation.".IEEE ACCESS (2017).