Skew log-normal channel model for indoor cooperative localization

Sung, CK; Li, S; Hedley, M; Nikolic, N; Ni, W

Skew log-normal channel model for indoor cooperative localization

Sung, CK Li, S Hedley, M Nikolic, N Ni, W

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Publication Type:: Conference Proceeding
Citation:: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, 2018, 2017-October pp. 1 - 5
Issue Date:: 2018-02-14

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Field	Value	Language
dc.contributor.author	Sung, CK	en_US
dc.contributor.author	Li, S	en_US
dc.contributor.author	Hedley, M	en_US
dc.contributor.author	Nikolic, N	en_US
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X	en_US
dc.date.issued	2018-02-14	en_US
dc.identifier.citation	IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, 2018, 2017-October pp. 1 - 5	en_US
dc.identifier.isbn	9781538635315	en_US
dc.identifier.uri	http://hdl.handle.net/10453/128530
dc.description.abstract	© 2017 IEEE. The performance of cooperative localization using received signal strength (RSS) benefits from accurate radio channel modeling. While log-normal shadowing is commonly used to model the relationship between RSS and range, the RSS error distribution in indoor environments has been observed to be neither normal nor symmetric. In this paper, we propose a skew log-normal channel model, which includes the standard log-normal model as a special case. We further propose an algorithm for using this model for RSS based cooperative localization. The algorithm was evaluated using data from an electro-magnetic simulation of an aircraft cabin, and was shown to generate more accurate node locations compared to the use of log-normal shadowing in the same localization algorithm.	en_US
dc.relation.ispartof	IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC	en_US
dc.relation.isbasedon	10.1109/PIMRC.2017.8292294	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Skew log-normal channel model for indoor cooperative localization	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2017-October	en_US
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	2017-October	en_US

Abstract:

© 2017 IEEE. The performance of cooperative localization using received signal strength (RSS) benefits from accurate radio channel modeling. While log-normal shadowing is commonly used to model the relationship between RSS and range, the RSS error distribution in indoor environments has been observed to be neither normal nor symmetric. In this paper, we propose a skew log-normal channel model, which includes the standard log-normal model as a special case. We further propose an algorithm for using this model for RSS based cooperative localization. The algorithm was evaluated using data from an electro-magnetic simulation of an aircraft cabin, and was shown to generate more accurate node locations compared to the use of log-normal shadowing in the same localization algorithm.

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http://hdl.handle.net/10453/128530