Please use this identifier to cite or link to this item: https://doi.org/10.1109/TWC.2010.03.090197
Title: Indoor localization with channel impulse response based fingerprint and nonparametric regression
Authors: Jin, Y.
Soh, W.-S. 
Wong, W.-C. 
Keywords: Channel impulse response
Fingerprinting
Indoor localization
Nonparametric kernel regression
Issue Date: Mar-2010
Source: Jin, Y., Soh, W.-S., Wong, W.-C. (2010-03). Indoor localization with channel impulse response based fingerprint and nonparametric regression. IEEE Transactions on Wireless Communications 9 (3) : 1120-1127. ScholarBank@NUS Repository. https://doi.org/10.1109/TWC.2010.03.090197
Abstract: In this paper, we propose a fingerprint-based localization scheme that exploits the location dependency of the channel impulse response (CIR). We approximate the CIR by applying Inverse Fourier Transform to the receivers channel estimation. The amplitudes of the approximated CIR (ACIR) vector are further transformed into the logarithmic scale to ensure that elements in the ACIR vector contribute fairly to the location estimation, which is accomplished through Nonparametric Kernel Regression. As shown in our simulations, when both the number of access points and density of training locations are the same, our proposed scheme displays significant advantages in localization accuracy, compared to other fingerprint-based methods found in the literature. Moreover, absolute localization accuracy of the proposed scheme is shown to be resilient to the real time environmental changes caused by human bodies with random positions and orientations. © 2006 IEEE.
Source Title: IEEE Transactions on Wireless Communications
URI: http://scholarbank.nus.edu.sg/handle/10635/56321
ISSN: 15361276
DOI: 10.1109/TWC.2010.03.090197
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

60
checked on Dec 7, 2017

WEB OF SCIENCETM
Citations

49
checked on Nov 23, 2017

Page view(s)

28
checked on Dec 11, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.