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Position estimation and tracking of an autonomous mobile sensor using received signal strength

Black, Timothy J., Pathirana, Pubudu and Nahavandi, Saeid 2008, Position estimation and tracking of an autonomous mobile sensor using received signal strength, in ISSNIP 2008 : IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, IEEE, Piscataway, N.J., pp. 19-24, doi: 10.1109/ISSNIP.2008.4761956.

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Title Position estimation and tracking of an autonomous mobile sensor using received signal strength
Author(s) Black, Timothy J.
Pathirana, PubuduORCID iD for Pathirana, Pubudu orcid.org/0000-0001-8014-7798
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Conference name IEEE Conference on Intelligent Sensors, Sensor Networks and Information Processing (2008 : Sydney, N.S.W.)
Conference location Sydney, N.S.W.
Conference dates 15-18 December 2008
Title of proceedings ISSNIP 2008 : IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing
Editor(s) Bouzerdoum, A.
Palaniswami, M.
Dissanayake, G.
Sowmya, A.
Publication date 2008
Conference series IEEE Conference on Intelligent Sensors, Sensor Networks and Information Processing
Start page 19
End page 24
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Summary In this paper, an algorithm for approximating the path of a moving autonomous mobile sensor with an unknown position location using Received Signal Strength (RSS) measurements is proposed. Using a Least Squares (LS) estimation method as an input, a Maximum-Likelihood (ML) approach is used to determine the location of the unknown mobile sensor. For the mobile sensor case, as the sensor changes position the characteristics of the RSS measurements also change; therefore the proposed method adapts the RSS measurement model by dynamically changing the pass loss value alpha to aid in position estimation. Secondly, a Recursive Least-Squares (RLS) algorithm is used to estimate the path of a moving mobile sensor using the Maximum-Likelihood position estimation as an input. The performance of the proposed algorithm is evaluated via simulation and it is shown that this method can accurately determine the position of the mobile sensor, and can efficiently track the position of the mobile sensor during motion.
Notes ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 9781424429578
Language eng
DOI 10.1109/ISSNIP.2008.4761956
Field of Research 080503 Networking and Communications
Socio Economic Objective 861799 Communication Equipment not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2008, IEEE
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30018212

Document type: Conference Paper
Collections: School of Engineering and Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.