Estimators of compound Gaussian clutter with lognormal texture
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Date
2019
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Journal ISSN
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Publisher
Université de M'sila
Abstract
Estimators of clutter models parameters based upon higher order
moments estimator (HOME) produce usually poor results in particular
for low sample sizes. In an attempt to remedy this situation,
closed forms of [zlog(z)] and fractional order moments estimator
(FOME) are derived in this work and yield a good estimation
accuracy of parameters of the compound Gaussian clutter with
log-normal texture (CG-LNT). Using simulated and real data, estimation
comparisons show that best values of mean square error
(MSE) and bias are achieved using the proposed procedures.