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Statistical Analysis of Bistatic Radar Ground Clutter for Different German Rural Environments

This article presents the statistical analysis of bistatic radar rural ground clutter for different terrain types under low grazing angles. Compared to most state-of-the-art analysis, we present country-specific clutter analysis for subgroups of rural environments rather than for the rural environme...

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Autores principales: Kohler, Michael, O’Hagan, Daniel W., Weiss, Matthias, Wegner, David, Worms, Josef, Bringmann, Oliver
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309089/
https://www.ncbi.nlm.nih.gov/pubmed/32532081
http://dx.doi.org/10.3390/s20113311
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author Kohler, Michael
O’Hagan, Daniel W.
Weiss, Matthias
Wegner, David
Worms, Josef
Bringmann, Oliver
author_facet Kohler, Michael
O’Hagan, Daniel W.
Weiss, Matthias
Wegner, David
Worms, Josef
Bringmann, Oliver
author_sort Kohler, Michael
collection PubMed
description This article presents the statistical analysis of bistatic radar rural ground clutter for different terrain types under low grazing angles. Compared to most state-of-the-art analysis, we present country-specific clutter analysis for subgroups of rural environments rather than for the rural environment as a whole. Therefore, the rural environment analysis is divided into four dominant subgroup terrain types, namely fields with low vegetation, fields with high vegetation, plantations of small trees and forest environments representing a typical rural German environment. We will present the results for both the summer and the winter vegetation. Therefore, bistatic measurement campaigns have been carried out during the summer 2019 and the winter of 2019/20 in the aforementioned four different rural terrain types. The measurements were performed in the radar relevant X-band at a center frequency of 8.85 GHz and over a bandwidth of 100 MHz according to available transmit permission. The distinction of the rural terrain into different subgroups enables a more precise and accurate clutter analysis and modeling of the statistical properties as will be shown in the presented results. The statistical properties are derived from the calculated clutter amplitudes probability density functions and corresponding cumulative distribution functions for each of the four terrain types and the corresponding season. The data basis for the clutter analysis are the processed range-Doppler maps from the bistatic radar measurements. According to the authors’ current knowledge, a similar investigation based on real bistatic radar measurement data with the division into terrain subgroups has not yet been carried out and published for a German rural environment.
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spelling pubmed-73090892020-06-25 Statistical Analysis of Bistatic Radar Ground Clutter for Different German Rural Environments Kohler, Michael O’Hagan, Daniel W. Weiss, Matthias Wegner, David Worms, Josef Bringmann, Oliver Sensors (Basel) Article This article presents the statistical analysis of bistatic radar rural ground clutter for different terrain types under low grazing angles. Compared to most state-of-the-art analysis, we present country-specific clutter analysis for subgroups of rural environments rather than for the rural environment as a whole. Therefore, the rural environment analysis is divided into four dominant subgroup terrain types, namely fields with low vegetation, fields with high vegetation, plantations of small trees and forest environments representing a typical rural German environment. We will present the results for both the summer and the winter vegetation. Therefore, bistatic measurement campaigns have been carried out during the summer 2019 and the winter of 2019/20 in the aforementioned four different rural terrain types. The measurements were performed in the radar relevant X-band at a center frequency of 8.85 GHz and over a bandwidth of 100 MHz according to available transmit permission. The distinction of the rural terrain into different subgroups enables a more precise and accurate clutter analysis and modeling of the statistical properties as will be shown in the presented results. The statistical properties are derived from the calculated clutter amplitudes probability density functions and corresponding cumulative distribution functions for each of the four terrain types and the corresponding season. The data basis for the clutter analysis are the processed range-Doppler maps from the bistatic radar measurements. According to the authors’ current knowledge, a similar investigation based on real bistatic radar measurement data with the division into terrain subgroups has not yet been carried out and published for a German rural environment. MDPI 2020-06-10 /pmc/articles/PMC7309089/ /pubmed/32532081 http://dx.doi.org/10.3390/s20113311 Text en © 2020 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
Kohler, Michael
O’Hagan, Daniel W.
Weiss, Matthias
Wegner, David
Worms, Josef
Bringmann, Oliver
Statistical Analysis of Bistatic Radar Ground Clutter for Different German Rural Environments
title Statistical Analysis of Bistatic Radar Ground Clutter for Different German Rural Environments
title_full Statistical Analysis of Bistatic Radar Ground Clutter for Different German Rural Environments
title_fullStr Statistical Analysis of Bistatic Radar Ground Clutter for Different German Rural Environments
title_full_unstemmed Statistical Analysis of Bistatic Radar Ground Clutter for Different German Rural Environments
title_short Statistical Analysis of Bistatic Radar Ground Clutter for Different German Rural Environments
title_sort statistical analysis of bistatic radar ground clutter for different german rural environments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309089/
https://www.ncbi.nlm.nih.gov/pubmed/32532081
http://dx.doi.org/10.3390/s20113311
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