Open AccessLow‐order moment‐based estimation of shape parameter of CGIG clutter model
Author(s) -
Yu Han,
Shui PengLang,
Huang YuTing
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2016.2248
Subject(s) - clutter , moment (physics) , estimator , gaussian , estimation theory , algorithm , mathematics , method of moments (probability theory) , computer science , radar , statistics , physics , telecommunications , classical mechanics , quantum mechanics
In this Letter, a low‐order moment‐based estimation of the parameters of compound‐Gaussian clutter model with the inverse Gaussian texture (CGIG) is proposed. The CGIG clutter model proposed recently was known as an effective model to describe high‐resolution sea clutter at low grazing angles. Its parameter estimation is often obtained by the explicit moment‐based estimation using the second‐ and fourth‐order moments, which is low precision in the case of small samples. Here, the first‐ and second‐order moments are used to construct a higher precision estimator, where the look‐up table method is employed to make up the lack of explicit expression of the shape parameter.