Estimation of K-distributed clutter by using characteristic function method

Detection performance of the maritime radars is often limited by the unwanted sea echo or clutter. K-distribution is one of the long-tailed densities which is known in the signal processing community for fitting the radar sea clutter accurately. In this paper, a novel approach for estimating the par...

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Main Author: Marhaban, Mohammad Hamiruce
Format: Article
Language:English
Published: Universiti Teknologi Malaysia 2008
Online Access:http://psasir.upm.edu.my/id/eprint/14571/1/Estimation%20of%20K-distributed%20clutter%20by%20using%20characteristic%20function%20method.pdf
http://psasir.upm.edu.my/id/eprint/14571/
https://jurnalteknologi.utm.my/index.php/jurnalteknologi/article/view/223
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spelling my.upm.eprints.145712019-04-08T08:53:03Z http://psasir.upm.edu.my/id/eprint/14571/ Estimation of K-distributed clutter by using characteristic function method Marhaban, Mohammad Hamiruce Detection performance of the maritime radars is often limited by the unwanted sea echo or clutter. K-distribution is one of the long-tailed densities which is known in the signal processing community for fitting the radar sea clutter accurately. In this paper, a novel approach for estimating the parameter of K-distribution is presented. The method is derived from the empirical characteristic function of the quadrature components. Simulation results show a great improvement in term of estimated bias and variance, compared with any existing non-maximum likelihood method. Universiti Teknologi Malaysia 2008 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/14571/1/Estimation%20of%20K-distributed%20clutter%20by%20using%20characteristic%20function%20method.pdf Marhaban, Mohammad Hamiruce (2008) Estimation of K-distributed clutter by using characteristic function method. Jurnal Teknologi, 48 (D). pp. 29-40. ISSN 0127–9696; ESSN: 2180–3722 https://jurnalteknologi.utm.my/index.php/jurnalteknologi/article/view/223 10.11113/jt.v48.223
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Detection performance of the maritime radars is often limited by the unwanted sea echo or clutter. K-distribution is one of the long-tailed densities which is known in the signal processing community for fitting the radar sea clutter accurately. In this paper, a novel approach for estimating the parameter of K-distribution is presented. The method is derived from the empirical characteristic function of the quadrature components. Simulation results show a great improvement in term of estimated bias and variance, compared with any existing non-maximum likelihood method.
format Article
author Marhaban, Mohammad Hamiruce
spellingShingle Marhaban, Mohammad Hamiruce
Estimation of K-distributed clutter by using characteristic function method
author_facet Marhaban, Mohammad Hamiruce
author_sort Marhaban, Mohammad Hamiruce
title Estimation of K-distributed clutter by using characteristic function method
title_short Estimation of K-distributed clutter by using characteristic function method
title_full Estimation of K-distributed clutter by using characteristic function method
title_fullStr Estimation of K-distributed clutter by using characteristic function method
title_full_unstemmed Estimation of K-distributed clutter by using characteristic function method
title_sort estimation of k-distributed clutter by using characteristic function method
publisher Universiti Teknologi Malaysia
publishDate 2008
url http://psasir.upm.edu.my/id/eprint/14571/1/Estimation%20of%20K-distributed%20clutter%20by%20using%20characteristic%20function%20method.pdf
http://psasir.upm.edu.my/id/eprint/14571/
https://jurnalteknologi.utm.my/index.php/jurnalteknologi/article/view/223
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score 13.18916