Multidimensional vector regression for accurate and low-cost location estimation in pervasive computing

	Multidimensional vector regression for accurate and low-cost location estimation in pervasive computing
	Pan, Jeffrey Junfeng ; Kwok, James T.; Yang, Qiang ; Chen, Yiqiang
	2006-09-01
发表期刊	IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
ISSN	1041-4347
卷号	18 期号:9 页码:1181-1193
摘要	In this paper, we present an algorithm for multidimensional vector regression on data that are highly uncertain and nonlinear, and then apply it to the problem of indoor location estimation in a wireless local area network (WLAN). Our aim is to obtain an accurate mapping between the signal space and the physical space without requiring too much human calibration effort. This location estimation problem has traditionally been tackled through probabilistic models trained on manually labeled data, which are expensive to obtain. In contrast, our algorithm adopts Kernel Canonical Correlation Analysis (KCCA) to build a nonlinear mapping between the signal-vector space and the physical location space by transforming data in both spaces into their canonical features. This allows the pairwise similarity of samples in both spaces to be maximally correlated using kernels. We use a Gaussian kernel to adapt to the noisy characteristics of signal strengths and a Matern kernel to sense the changes in physical locations. By using real data collected in an 802.11 wireless LAN environment, we achieve accurate location estimation for pervasive computing while requiring a much smaller set of labeled training data than previous methods.
关键词	location-dependent and sensitive correlation and regression analysis pervasive computing
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS记录号	WOS:000239077800003
出版者	IEEE COMPUTER SOC
引用统计	被引频次：80[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/10754
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Pan, Jeffrey Junfeng
作者单位	1.Hong Kong Univ Sci & Technol, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China 2.Chinese Acad Sci, Comp Technol Inst, Shanghai Branch, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Pan, Jeffrey Junfeng,Kwok, James T.,Yang, Qiang,et al. Multidimensional vector regression for accurate and low-cost location estimation in pervasive computing[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2006,18(9):1181-1193.
APA	Pan, Jeffrey Junfeng,Kwok, James T.,Yang, Qiang,&Chen, Yiqiang.(2006).Multidimensional vector regression for accurate and low-cost location estimation in pervasive computing.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,18(9),1181-1193.
MLA	Pan, Jeffrey Junfeng,et al."Multidimensional vector regression for accurate and low-cost location estimation in pervasive computing".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 18.9(2006):1181-1193.