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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| Format: | Article |
| Language: | English |
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Universiti Teknologi Malaysia
2008
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| Online Access: | http://psasir.upm.edu.my/id/eprint/14571/ http://psasir.upm.edu.my/id/eprint/14571/1/Estimation%20of%20K-distributed%20clutter%20by%20using%20characteristic%20function%20method.pdf |
| _version_ | 1848842430764285952 |
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| author | Marhaban, Mohammad Hamiruce |
| author_facet | Marhaban, Mohammad Hamiruce |
| author_sort | Marhaban, Mohammad Hamiruce |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T07:59:01Z |
| format | Article |
| id | upm-14571 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T07:59:01Z |
| publishDate | 2008 |
| publisher | Universiti Teknologi Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| spellingShingle | Marhaban, Mohammad Hamiruce Estimation of K-distributed clutter by using characteristic function method |
| title | 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_short | Estimation of K-distributed clutter by using characteristic function method |
| title_sort | estimation of k-distributed clutter by using characteristic function method |
| url | http://psasir.upm.edu.my/id/eprint/14571/ http://psasir.upm.edu.my/id/eprint/14571/ http://psasir.upm.edu.my/id/eprint/14571/ http://psasir.upm.edu.my/id/eprint/14571/1/Estimation%20of%20K-distributed%20clutter%20by%20using%20characteristic%20function%20method.pdf |