Liu, C., Kiring, A., Salman, N. et al. (2 more authors) (2016) A Kriging Algorithm for Fingerprinting Positioning with received Signal Strengths. In: Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2015. Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2015, 06-08 Oct 2015, Bonn, Germany. IEEE
Abstract
Abstract—Received signal strength (RSS) based location fingerprinting is a powerful wireless positioning technique. It estimates the target location by consulting a preliminary database and searching for the best matched RSS fingerprints. The construction and maintenance of a sufficient fingerprint database could be laborious and problematic. This paper proposes a new approach that utilizes the Kriging spatial interpolation algorithm to build complete fingerprint databases from sparsely collected measurements. The interpolation performance is analyzed over various extents of sparsity and number of measurements. The constructed fingerprint databases are utilized to locate a static target and the localization performances are analyzed. It is shown that the Kriging algorithm can be used to build RSS fingerprint databases of good accuracy based on sparsely collected measurements.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works |
Keywords: | Krigging method; Localisation; Wireless Sensor Networks; Correlated Measurements |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Feb 2016 16:24 |
Last Modified: | 19 Dec 2022 13:32 |
Published Version: | http://dx.doi.org/10.1109/SDF.2015.7347695 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/SDF.2015.7347695 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:93486 |