Khan, MW, Kemp, AH and Salman, N (2017) Optimized hybrid localisation with cooperation in wireless sensor networks. IET Signal Processing, 11 (3). pp. 341-348. ISSN 1751-9675
Abstract
In this study, the authors introduce a novel hybrid cooperative localisation scheme when both distance and angle measurements are available. Two linear least squares (LLS) hybrid cooperative schemes based on angle of arrival–time of arrival (AoA–ToA) and AoA–received signal strength (AoA–RSS) signals are proposed. The proposed algorithms are modified to accommodate cooperative localisation in resource constrained networks where only distance measurements are available between target sensors (TSs) while both distance and angle measurements are available between reference sensors and TSs. Furthermore, an optimised version of the LLS estimator is proposed to further enhance the localisation performance. Moreover, localisation of sensor nodes in networks with limited connectivity (partially connected networks) is also investigated. Finally, computational complexity analysis of the proposed algorithms is presented. Through simulation, the superior performance of the proposed algorithms over its non-cooperative counterpart and the hybrid signal based iterative non-linear least squares algorithms is demonstrated.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Institution of Engineering and Technology. This paper is a postprint of a paper submitted to and accepted for publication in IET Signal Processing and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library. |
Keywords: | wireless sensor networks; iterative methods; least squares approximations; hybrid signal based iterative nonlinear least squares algorithms; novel hybrid cooperative localisation scheme; LLS estimator; linear least squares hybrid cooperative schemes; target sensors; computational complexity analysis; wireless sensor networks |
Dates: |
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Institution: | The University of Leeds |
Funding Information: | Funder Grant number EPSRC EP/K004832/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Jun 2017 12:06 |
Last Modified: | 04 Feb 2018 08:04 |
Status: | Published |
Publisher: | Institution of Engineering and Technology |
Identification Number: | 10.1049/iet-spr.2015.0390 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:117181 |