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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Universiti Teknologi Malaysia
2008
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| 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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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 |
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| 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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