NDLI: Indoor Fingerprinting Geolocation using Wavelet-Based Features Extracted from the Channel Impulse Response in Conjunction with an Artificial Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Nerguizian, C. Nerguizian, V.
Copyright Year	2007
Description	Author affiliation: Ecole Polytechnique de Montreal, Montreal (Nerguizian, C.)
Abstract	This paper proposes a method to localize a mobile station in an indoor environment using wavelet- based features (WBF) extracted from the channel impulse response (CIR) in conjunction with an artificial neural network (ANN). The proposed localization system makes use of the fingerprinting technique and employs CIR information as the signature and an artificial neural network as the pattern matching algorithm. For the considered indoor environment, the obtained CIR information can not be applied directly to the input of the ANN due to the high number of the CIR samples since an ANN with a high number of inputs requires a high number of learning patterns during its training. Consequently, relevant features reflecting the CIR signature have to be extracted and then applied to the ANN. The relevant features may be some physical channel parameters or a compressed version of the CIR signature. In this paper, the extraction of the CIR features is done using a wavelet-based compression. The particularity of the method is in the representation of the CIR signature in a judicious way facilitating the design of the ANN. Moreover, when the extracted features correspond to the CIR signature, the localization system tends to give mobile location with a high precision. Simulation of measured CIR in an indoor environment, showed a precision of 2 meters for 91% and 70% of trained and untrained data, respectively.
Starting Page	2028
Ending Page	2032
File Size	210645
Page Count	5
File Format	PDF
ISBN	9781424407545
DOI	10.1109/ISIE.2007.4374919
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-06-04
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fingerprint recognition Feature extraction Artificial neural networks Indoor environments Data mining Databases Pattern matching Real time systems Intelligent networks Chemical technology
Content Type	Text
Resource Type	Article

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