Maximum likelihood localization of wireless networks using biased range measurements

Anthony J. Weiss; Joseph S. Picard

doi:10.1109/ISCIT.2007.4392137

Maximum likelihood localization of wireless networks using biased range measurements

Anthony J. Weiss, Joseph S. Picard

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Localization of ad-hoc wireless networks is useful for services, management and routing. Localization is frequently based on station-to-station range measurements and a few reference sensors. We address the localization problem in the case of incomplete set of noisy range measurements with unknown bias. A statistically efficient, Maximum Likelihood algorithm, inspired by the Gerchberg-Saxton procedure for phase retrieval, is presented. In addition, a compact explicit expression for the Fisher Information matrix is provided. A set of numerical examples demonstrates the bias effect on the localization accuracy. As expected, the localization accuracy improves when the unknown bias is estimated.

Original language	English
Title of host publication	ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings
Pages	865-870
Number of pages	6
DOIs	https://doi.org/10.1109/ISCIT.2007.4392137
State	Published - 2007
Event	ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies - Sydney, Australia Duration: 16 Oct 2007 → 19 Oct 2007

Publication series

Name	ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings

Conference

Conference	ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies
Country/Territory	Australia
City	Sydney
Period	16/10/07 → 19/10/07

Keywords

Ad-hoc mobile networks
Location estimation
Maximum likelihood estimation
Wireless sensor network

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10.1109/ISCIT.2007.4392137

Cite this

Weiss, A. J., & Picard, J. S. (2007). Maximum likelihood localization of wireless networks using biased range measurements. In ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings (pp. 865-870). Article 4392137 (ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings). https://doi.org/10.1109/ISCIT.2007.4392137

@inproceedings{67234fabc96643518842475badfae40d,

title = "Maximum likelihood localization of wireless networks using biased range measurements",

abstract = "Localization of ad-hoc wireless networks is useful for services, management and routing. Localization is frequently based on station-to-station range measurements and a few reference sensors. We address the localization problem in the case of incomplete set of noisy range measurements with unknown bias. A statistically efficient, Maximum Likelihood algorithm, inspired by the Gerchberg-Saxton procedure for phase retrieval, is presented. In addition, a compact explicit expression for the Fisher Information matrix is provided. A set of numerical examples demonstrates the bias effect on the localization accuracy. As expected, the localization accuracy improves when the unknown bias is estimated.",

keywords = "Ad-hoc mobile networks, Location estimation, Maximum likelihood estimation, Wireless sensor network",

author = "Weiss, {Anthony J.} and Picard, {Joseph S.}",

year = "2007",

doi = "10.1109/ISCIT.2007.4392137",

language = "אנגלית",

isbn = "1424409772",

series = "ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings",

pages = "865--870",

booktitle = "ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings",

note = "ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies ; Conference date: 16-10-2007 Through 19-10-2007",

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Weiss, AJ & Picard, JS 2007, Maximum likelihood localization of wireless networks using biased range measurements. in ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings., 4392137, ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings, pp. 865-870, ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies, Sydney, Australia, 16/10/07. https://doi.org/10.1109/ISCIT.2007.4392137

Maximum likelihood localization of wireless networks using biased range measurements. / Weiss, Anthony J.; Picard, Joseph S.
ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings. 2007. p. 865-870 4392137 (ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Localization of ad-hoc wireless networks is useful for services, management and routing. Localization is frequently based on station-to-station range measurements and a few reference sensors. We address the localization problem in the case of incomplete set of noisy range measurements with unknown bias. A statistically efficient, Maximum Likelihood algorithm, inspired by the Gerchberg-Saxton procedure for phase retrieval, is presented. In addition, a compact explicit expression for the Fisher Information matrix is provided. A set of numerical examples demonstrates the bias effect on the localization accuracy. As expected, the localization accuracy improves when the unknown bias is estimated.

KW - Ad-hoc mobile networks

KW - Location estimation

KW - Maximum likelihood estimation

KW - Wireless sensor network

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BT - ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings

T2 - ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies

Y2 - 16 October 2007 through 19 October 2007

ER -

Weiss AJ, Picard JS. Maximum likelihood localization of wireless networks using biased range measurements. In ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings. 2007. p. 865-870. 4392137. (ISCIT 2007 - 2007 International Symposium on Communications and Information Technologies Proceedings). doi: 10.1109/ISCIT.2007.4392137

Maximum likelihood localization of wireless networks using biased range measurements

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Keywords

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