A Parameter Estimation Method for K-Distribution
Summary :
Estimating the parameters of a statistical distribution from measured sample values forms an essential part of many signal processing tasks. K-distribution has been proven to be an appropriate model for characterising the amplitude of sea clutter. In this paper, a new method for estimating the parameters of K-Distribution is proposed. The method greatly lowers the computational requirement and variance of parameter estimates when compared with the existing non-maximum likelihood methods.
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- IEICE TRANSACTIONS on Communications Vol.E87-B No.10 pp.3158-3162
- Publication Date
- 2004/10/01
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- LETTER
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- Sensing
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Mohammad H. MARHABAN, "A Parameter Estimation Method for K-Distribution" in IEICE TRANSACTIONS on Communications,
vol. E87-B, no. 10, pp. 3158-3162, October 2004, doi: .
Abstract: Estimating the parameters of a statistical distribution from measured sample values forms an essential part of many signal processing tasks. K-distribution has been proven to be an appropriate model for characterising the amplitude of sea clutter. In this paper, a new method for estimating the parameters of K-Distribution is proposed. The method greatly lowers the computational requirement and variance of parameter estimates when compared with the existing non-maximum likelihood methods.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e87-b_10_3158/_p
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@ARTICLE{e87-b_10_3158,
author={Mohammad H. MARHABAN, },
journal={IEICE TRANSACTIONS on Communications},
title={A Parameter Estimation Method for K-Distribution},
year={2004},
volume={E87-B},
number={10},
pages={3158-3162},
abstract={Estimating the parameters of a statistical distribution from measured sample values forms an essential part of many signal processing tasks. K-distribution has been proven to be an appropriate model for characterising the amplitude of sea clutter. In this paper, a new method for estimating the parameters of K-Distribution is proposed. The method greatly lowers the computational requirement and variance of parameter estimates when compared with the existing non-maximum likelihood methods.},
keywords={},
doi={},
ISSN={},
month={October},}
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TY - JOUR
TI - A Parameter Estimation Method for K-Distribution
T2 - IEICE TRANSACTIONS on Communications
SP - 3158
EP - 3162
AU - Mohammad H. MARHABAN
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E87-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2004
AB - Estimating the parameters of a statistical distribution from measured sample values forms an essential part of many signal processing tasks. K-distribution has been proven to be an appropriate model for characterising the amplitude of sea clutter. In this paper, a new method for estimating the parameters of K-Distribution is proposed. The method greatly lowers the computational requirement and variance of parameter estimates when compared with the existing non-maximum likelihood methods.
ER -
English
