SHAPE PARAMETER ESTIMATION FOR K-DISTRIBUTION USING VARIATIONAL BAYESIAN APPROACH

被引：0
|
作者：
Turlapaty, Anish C. [1 ]
机构：
[1] Indian Inst Informat Technol Sri City, Sri City, Andhra Pradesh, India
来源：
2018 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP) | 2018年
关键词：
K-distribution; clutter; parameter estimation; variational bayesian;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The sea clutter component in some of the radar and sonar signal models can be statistically characterized as following a K-distribution. This distribution has a shape parameter that is directly related to the number of scatterers. Hence, the estimation of this shape parameter is an important problem and is traditionally addressed using the maximum likelihood (ML), the method of moments (MoM) and their variants. A short-coming of these methods is lesser accuracy in comparison to the theoretical CRB. In this paper, a variational Bayesian algorithm is proposed that provides both improved convergence and superior accuracy in comparison to the existing algorithms.
引用
收藏
页码：243 / 247
页数：5
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