NDLI: Axial decoupled LS-SVMs for indoor positioning using RSS fingerprints

Content Provider	IEEE Xplore Digital Library
Author	Wei Yanhua Wang Dongli Zhou Yan
Copyright Year	2015
Description	Author affiliation: Coll. of Inf. Eng., Xiangtan Univ., Xiangtan, China (Wei Yanhua; Wang Dongli; Zhou Yan)
Abstract	Location fingerprints based indoor positioning, which uses received signal strength (RSS) from wireless access points (APs), has become a hot research topic during the last a few years. Statistical learning based technique is one of the popular and effective methods for fingerprinting localization. Unfortunately, they suffer from high computational burden and require a large number of classifiers to determine the object location. To handle this problem, axial decoupled least squares support vector machines (AD-LS-SVM) based fingerprinting localization is proposed in this paper. First, the framework of fingerprinting localization based on AD-LS-SVM is given. Then, the decoupled training and positioning process by fingerprinting samples is described in detail. The attention is focused on how to transfer the positioning problem to a multi-class classification problem, for which we adopt two popular approaches: one-against-one (OAO) and one-against-all (OAA). Experimental results show that the proposed AD-LS-SVM method has the highest location accuracy among the traditional Grid LS-SVM, Support Vector Machines (SVMs) and the popular k-nearest neighbors (k-NNs), while requires much smaller training time.
Starting Page	3920
Ending Page	3925
File Size	326216
Page Count	6
File Format	PDF
ISBN	9789881563897
ISSN	19341768
DOI	10.1109/ChiCC.2015.7260244
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Technical Committee on Control Theory, Chinese Association of Automation
Subject Keyword	Decision support systems Training localization Accuracy RSS LS-SVM Fingerprint recognition Location fingerprint indoor positioning Testing
Content Type	Text
Resource Type	Article

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