Title: Modeling and Parameter Estimation of Radar Sea-Clutter with Trimodal Gamma Population, Journal of Telecommunications and Information Technology, 2022, nr 2


Real radar data often consist of a mixture of Gaussian and non-Gaussian clutter. Such a situation creates one or more inflexion points in the curve of the empirical cumulative distributed function (CDF). In order to obtain an accurate fit with sea reverberation data, we propose, in this paper, a trimodal gamma disturbance model and two parameter estimators. The non-linear least-squares (NLS) fit approach is used to avoid computational issues associated with the maximum likelihood estimator (MLE) and moments-based estimator for parameters of the mixture model. For this purpose, a combination of moment fit and complementary CDF (CCDF) NLS fit methods is proposed. The simplex minimization algorithm is used to simultaneously obtain all parameters of the model. In the case of a single gamma probability density function, a zlog(z) method is derived. Firstly, simulated life tests based on a gamma population with different shape parameter values are worked out. Then, numerical illustrations show that both MLE and zlog(z) methods produce closer results. The proposed trimodal gamma distribution with moments NLS fit and CCDF NLS fit estimators is validated to be in qualitative agreement with different cell resolutions of the available IPIX database.


Instytut Łączności - Państwowy Instytut Badawczy



Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:2229


Journal of Telecommunications and Information Technology



Rights Management:

Biblioteka Naukowa Instytutu Łączności

Object collections:

Last modified:

Mar 12, 2024

In our library since:

Jul 21, 2022

Number of object content hits:


All available object's versions:


Show description in RDF format:


Show description in OAI-PMH format:


Objects Similar



Citation style:

This page uses 'cookies'. More information