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An Improved Performance Frequency Estimation Algorithm for Passive Wireless SAW Resonant Sensors
Passive wireless surface acoustic wave (SAW) resonant sensors are suitable for applications in harsh environments. The traditional SAW resonant sensor system requires, however, Fourier transformation (FT) which has a resolution restriction and decreases the accuracy. In order to improve the accuracy...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299012/ https://www.ncbi.nlm.nih.gov/pubmed/25429410 http://dx.doi.org/10.3390/s141222261 |
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author | Liu, Boquan Zhang, Chenrui Ji, Xiaojun Chen, Jing Han, Tao |
author_facet | Liu, Boquan Zhang, Chenrui Ji, Xiaojun Chen, Jing Han, Tao |
author_sort | Liu, Boquan |
collection | PubMed |
description | Passive wireless surface acoustic wave (SAW) resonant sensors are suitable for applications in harsh environments. The traditional SAW resonant sensor system requires, however, Fourier transformation (FT) which has a resolution restriction and decreases the accuracy. In order to improve the accuracy and resolution of the measurement, the singular value decomposition (SVD)-based frequency estimation algorithm is applied for wireless SAW resonant sensor responses, which is a combination of a single tone undamped and damped sinusoid signal with the same frequency. Compared with the FT algorithm, the accuracy and the resolution of the method used in the self-developed wireless SAW resonant sensor system are validated. |
format | Online Article Text |
id | pubmed-4299012 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-42990122015-01-26 An Improved Performance Frequency Estimation Algorithm for Passive Wireless SAW Resonant Sensors Liu, Boquan Zhang, Chenrui Ji, Xiaojun Chen, Jing Han, Tao Sensors (Basel) Article Passive wireless surface acoustic wave (SAW) resonant sensors are suitable for applications in harsh environments. The traditional SAW resonant sensor system requires, however, Fourier transformation (FT) which has a resolution restriction and decreases the accuracy. In order to improve the accuracy and resolution of the measurement, the singular value decomposition (SVD)-based frequency estimation algorithm is applied for wireless SAW resonant sensor responses, which is a combination of a single tone undamped and damped sinusoid signal with the same frequency. Compared with the FT algorithm, the accuracy and the resolution of the method used in the self-developed wireless SAW resonant sensor system are validated. MDPI 2014-11-25 /pmc/articles/PMC4299012/ /pubmed/25429410 http://dx.doi.org/10.3390/s141222261 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( (http://creativecommons.org/licenses/by/4.0/) http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Boquan Zhang, Chenrui Ji, Xiaojun Chen, Jing Han, Tao An Improved Performance Frequency Estimation Algorithm for Passive Wireless SAW Resonant Sensors |
title | An Improved Performance Frequency Estimation Algorithm for Passive Wireless SAW Resonant Sensors |
title_full | An Improved Performance Frequency Estimation Algorithm for Passive Wireless SAW Resonant Sensors |
title_fullStr | An Improved Performance Frequency Estimation Algorithm for Passive Wireless SAW Resonant Sensors |
title_full_unstemmed | An Improved Performance Frequency Estimation Algorithm for Passive Wireless SAW Resonant Sensors |
title_short | An Improved Performance Frequency Estimation Algorithm for Passive Wireless SAW Resonant Sensors |
title_sort | improved performance frequency estimation algorithm for passive wireless saw resonant sensors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299012/ https://www.ncbi.nlm.nih.gov/pubmed/25429410 http://dx.doi.org/10.3390/s141222261 |
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