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Investigation into the Effect of Atmospheric Particulate Matter (PM(2.5) and PM(10)) Concentrations on GPS Signals
The Global Positioning System (GPS) has been widely used in navigation, surveying, geophysical and geodynamic studies, machine guidance, etc. High-precision GPS applications such as geodetic surveying need millimeter and centimeter level accuracy. Since GPS signals are affected by atmospheric effect...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375794/ https://www.ncbi.nlm.nih.gov/pubmed/28273798 http://dx.doi.org/10.3390/s17030508 |
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author | Lau, Lawrence He, Jun |
author_facet | Lau, Lawrence He, Jun |
author_sort | Lau, Lawrence |
collection | PubMed |
description | The Global Positioning System (GPS) has been widely used in navigation, surveying, geophysical and geodynamic studies, machine guidance, etc. High-precision GPS applications such as geodetic surveying need millimeter and centimeter level accuracy. Since GPS signals are affected by atmospheric effects, methods of correcting or eliminating ionospheric and tropospheric bias are needed in GPS data processing. Relative positioning can be used to mitigate the atmospheric effect, but its efficiency depends on the baseline lengths. Air pollution is a serious problem globally, especially in developing countries that causes health problems to humans and damage to the ecosystem. Respirable suspended particles are coarse particles with a diameter of 10 micrometers or less, also known as PM(10). Moreover, fine particles with a diameter of 2.5 micrometers or less are known as PM(2.5). GPS signals travel through the atmosphere before arriving at receivers on the Earth’s surface, and the research question posed in this paper is: are GPS signals affected by the increased concentration of the PM(2.5)/PM(10) particles? There is no standard model of the effect of PM(2.5)/PM(10) particles on GPS signals in GPS data processing, although an approximate generic model of non-gaseous atmospheric constituents (<1 mm) can be found in the literature. This paper investigates the effect of the concentration of PM(2.5)/PM(10) particles on GPS signals and validates the aforementioned approximate model with a carrier-to-noise ratio (CNR)-based empirical method. Both the approximate model and the empirical results show that the atmospheric PM(2.5)/PM(10) particles and their concentrations have a negligible effect on GPS signals and the effect is comparable with the noise level of GPS measurements. |
format | Online Article Text |
id | pubmed-5375794 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-53757942017-04-10 Investigation into the Effect of Atmospheric Particulate Matter (PM(2.5) and PM(10)) Concentrations on GPS Signals Lau, Lawrence He, Jun Sensors (Basel) Article The Global Positioning System (GPS) has been widely used in navigation, surveying, geophysical and geodynamic studies, machine guidance, etc. High-precision GPS applications such as geodetic surveying need millimeter and centimeter level accuracy. Since GPS signals are affected by atmospheric effects, methods of correcting or eliminating ionospheric and tropospheric bias are needed in GPS data processing. Relative positioning can be used to mitigate the atmospheric effect, but its efficiency depends on the baseline lengths. Air pollution is a serious problem globally, especially in developing countries that causes health problems to humans and damage to the ecosystem. Respirable suspended particles are coarse particles with a diameter of 10 micrometers or less, also known as PM(10). Moreover, fine particles with a diameter of 2.5 micrometers or less are known as PM(2.5). GPS signals travel through the atmosphere before arriving at receivers on the Earth’s surface, and the research question posed in this paper is: are GPS signals affected by the increased concentration of the PM(2.5)/PM(10) particles? There is no standard model of the effect of PM(2.5)/PM(10) particles on GPS signals in GPS data processing, although an approximate generic model of non-gaseous atmospheric constituents (<1 mm) can be found in the literature. This paper investigates the effect of the concentration of PM(2.5)/PM(10) particles on GPS signals and validates the aforementioned approximate model with a carrier-to-noise ratio (CNR)-based empirical method. Both the approximate model and the empirical results show that the atmospheric PM(2.5)/PM(10) particles and their concentrations have a negligible effect on GPS signals and the effect is comparable with the noise level of GPS measurements. MDPI 2017-03-03 /pmc/articles/PMC5375794/ /pubmed/28273798 http://dx.doi.org/10.3390/s17030508 Text en © 2017 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lau, Lawrence He, Jun Investigation into the Effect of Atmospheric Particulate Matter (PM(2.5) and PM(10)) Concentrations on GPS Signals |
title | Investigation into the Effect of Atmospheric Particulate Matter (PM(2.5) and PM(10)) Concentrations on GPS Signals |
title_full | Investigation into the Effect of Atmospheric Particulate Matter (PM(2.5) and PM(10)) Concentrations on GPS Signals |
title_fullStr | Investigation into the Effect of Atmospheric Particulate Matter (PM(2.5) and PM(10)) Concentrations on GPS Signals |
title_full_unstemmed | Investigation into the Effect of Atmospheric Particulate Matter (PM(2.5) and PM(10)) Concentrations on GPS Signals |
title_short | Investigation into the Effect of Atmospheric Particulate Matter (PM(2.5) and PM(10)) Concentrations on GPS Signals |
title_sort | investigation into the effect of atmospheric particulate matter (pm(2.5) and pm(10)) concentrations on gps signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375794/ https://www.ncbi.nlm.nih.gov/pubmed/28273798 http://dx.doi.org/10.3390/s17030508 |
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