Statistical analysis for terengganu forward scatter radar seaside clutter

The statistical analysis for Terengganu, Malaysia seaside clutter is presented in this paper. The measured clutter data were collected using a prototype of forward scatter radar (FSR) micro-sensor network with very high frequency (VHF) and ultra-high frequency (UHF) bands. Four categories of clutter...

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Published in:Jurnal Teknologi
Main Author: Ismail N.N.; Rashid N.E.A.; Khan Z.I.
Format: Article
Language:English
Published: Penerbit UTM Press 2016
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84970984342&doi=10.11113%2fjt.v78.8689&partnerID=40&md5=d3f90dcdf7f75fba3f9753f8685e109b
id 2-s2.0-84970984342
spelling 2-s2.0-84970984342
Ismail N.N.; Rashid N.E.A.; Khan Z.I.
Statistical analysis for terengganu forward scatter radar seaside clutter
2016
Jurnal Teknologi
78
5-Jul
10.11113/jt.v78.8689
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84970984342&doi=10.11113%2fjt.v78.8689&partnerID=40&md5=d3f90dcdf7f75fba3f9753f8685e109b
The statistical analysis for Terengganu, Malaysia seaside clutter is presented in this paper. The measured clutter data were collected using a prototype of forward scatter radar (FSR) micro-sensor network with very high frequency (VHF) and ultra-high frequency (UHF) bands. Four categories of clutter strength were recorded during the measurements, which are low, medium, strong and very strong clutter. The classes were divided according to the wind speed occurred during the measurements period. The analysis is to determine the best-fit distribution model for the measured clutter data. Four types of distribution models are used in this analysis, which are Weibull, Gamma, Log-Logistic and Log-Normal distribution. One of the goodness of fit (GOF) tests called root mean square error (RMSE) is used to prove which distribution is a better fit to the probability distribution of the measured clutter data. The obtained results show that for 64 MHz with all clutter level strength, Weibull distribution provides better fit and records the lowest RMSE. Weibull distribution also fits best to the clutter data for low clutter of 151 MHz. However, for the rest of clutter level strength for 151 MHz, Gamma distribution is the best-fitted model with lowest RMSE values. Log-Logistic distribution proves to be the best fitted model to all clutter level strength of clutter data for 434 MHz with smallest RMSE values. © 2016 Penerbit UTM Press. All rights reserved.
Penerbit UTM Press
1279696
English
Article
All Open Access; Bronze Open Access
author Ismail N.N.; Rashid N.E.A.; Khan Z.I.
spellingShingle Ismail N.N.; Rashid N.E.A.; Khan Z.I.
Statistical analysis for terengganu forward scatter radar seaside clutter
author_facet Ismail N.N.; Rashid N.E.A.; Khan Z.I.
author_sort Ismail N.N.; Rashid N.E.A.; Khan Z.I.
title Statistical analysis for terengganu forward scatter radar seaside clutter
title_short Statistical analysis for terengganu forward scatter radar seaside clutter
title_full Statistical analysis for terengganu forward scatter radar seaside clutter
title_fullStr Statistical analysis for terengganu forward scatter radar seaside clutter
title_full_unstemmed Statistical analysis for terengganu forward scatter radar seaside clutter
title_sort Statistical analysis for terengganu forward scatter radar seaside clutter
publishDate 2016
container_title Jurnal Teknologi
container_volume 78
container_issue 5-Jul
doi_str_mv 10.11113/jt.v78.8689
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84970984342&doi=10.11113%2fjt.v78.8689&partnerID=40&md5=d3f90dcdf7f75fba3f9753f8685e109b
description The statistical analysis for Terengganu, Malaysia seaside clutter is presented in this paper. The measured clutter data were collected using a prototype of forward scatter radar (FSR) micro-sensor network with very high frequency (VHF) and ultra-high frequency (UHF) bands. Four categories of clutter strength were recorded during the measurements, which are low, medium, strong and very strong clutter. The classes were divided according to the wind speed occurred during the measurements period. The analysis is to determine the best-fit distribution model for the measured clutter data. Four types of distribution models are used in this analysis, which are Weibull, Gamma, Log-Logistic and Log-Normal distribution. One of the goodness of fit (GOF) tests called root mean square error (RMSE) is used to prove which distribution is a better fit to the probability distribution of the measured clutter data. The obtained results show that for 64 MHz with all clutter level strength, Weibull distribution provides better fit and records the lowest RMSE. Weibull distribution also fits best to the clutter data for low clutter of 151 MHz. However, for the rest of clutter level strength for 151 MHz, Gamma distribution is the best-fitted model with lowest RMSE values. Log-Logistic distribution proves to be the best fitted model to all clutter level strength of clutter data for 434 MHz with smallest RMSE values. © 2016 Penerbit UTM Press. All rights reserved.
publisher Penerbit UTM Press
issn 1279696
language English
format Article
accesstype All Open Access; Bronze Open Access
record_format scopus
collection Scopus
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