NDLI: Parameter estimation of CGIG clutter plus noise using constrained NIOME and MLE approaches

Content Provider	IET Digital Library
Author	Mezache, Amar Gouri, Amel Oudira, Houcine
Abstract	Compound Gaussian inverse Gaussian (CGIG) distribution with thermal noise is well suited for sea clutter. The compact expression of higher order moments estimator (HOME) for CGIG clutter plus noise parameters is derived. When non-integer order moments (NIOM) are considered, numerical integration based on ‘Legendre’ and ‘Laguerre’ polynomials of Gauss quadrature method is employed. This estimator is referred to as constrained NIOM estimator (NIOME)-based method. Using the two first intensity moments, a constrained maximum likelihood estimator (CMLE) is formed by minimising the negative log likelihood function in one variable to obtain the shape parameter. For comparison purposes, computer simulations are presented with known and unknown clutter-to-noise ratio (CNR). In the case of known CNR, the method of moments provides a good fit as well as the NIOME and the CMLE methods. For unknown CNR, regardless the computing time, the HOME method is less accurate than the others. The constrained NIOME method requires numerical optimisation with acceptable calculation time. In most cases, the CMLE approach is accurate, but relatively slow due to the calculation of numerical integration of likelihood functions.
Starting Page	176
Ending Page	185
Page Count	10
ISSN	17518784
Volume Number	12
e-ISSN	17518792
Issue Number	Issue 2, Feb (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/12/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2017.0234
Journal	IET Radar, Sonar & Navigation
Publisher Date	2017-10-11
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	CGIG Clutter Plus Noise Parameter CGIG Distribution Clutter Compound Gaussian Inverse Gaussian Constrained NIOME Gauss Quadrature Method Gaussian Distribution Higher Order Moment Estimator HOME Intensity Moments Interpolation And Function Approximation Laguerre Polynomials Maximum Likelihood Estimation Maximum Likelihood Estimator MLE Approach Negative Log Likelihood Function NIOM Non-integer Order Moments Numerical Analysis Numerical Integration Parameter Estimation Polynomial Radar Radar Application Radar Equipment Sea Clutter Shape Parameter Statistics System And Application Thermal Noise
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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