STATISTICAL ANALYSIS FOR TERENGGANU FORWARD SCATTER RADAR SEASIDE CLUTTER
DOI:
https://doi.org/10.11113/jt.v78.8689Keywords:
Forward scatter radar, very high frequency, ultra-high frequency, Weibull, Gamma, Log-Logistic, Log-Normal, goodness of fit, root mean square error.Abstract
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.
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