Paper Info
Title
BORD: Bayesian optimum radar detector
Abstract
We derive the expression of an optimum non-Gaussian radar detector from the non-Gaussian spherically invariant random process (SIRP) clutter model and a Bayesian estimator of the SIRP characteristic density. SIRP modelizes non-Gaussian process as a complex Gaussian process whose variance, the so-called texture, is itself a positive random variable (r.v.). After performing a bayesian estimation of the texture probability density function (PDF) from reference clutter cells we derive the so-called Bayesian optimum radar detector (BORD) without any knowledge about the clutter statistics. We also derive the asymptotic expression of BORD (in law convergence), the so-called asymptotic BORD, as well as its theoretical performance (analytical threshold expression). BORD performance curves are shown for an unknown target signal embedded in correlated K-distributed and are compared with those of the optimum K-distributed detector. These results show that BORD reach optimal detector performances.
Year
DOI
Venue
2003
10.1016/S0165-1684(03)00034-3
Signal Processing
Keywords
Field
DocType
complex gaussian process,analytical threshold expression,optimal detector performance,sirp model,radar detection,clutter model,optimum non-gaussian radar detector,bord performance curve,bayesian optimum radar detector,optimum k-distributed detector,bayesian estimation,asymptotic expression,sirp characteristic density,clutter statistic,gaussian process,random variable,probability density function
Radar,Random variable,Control theory,Clutter,Stochastic process,Algorithm,Statistics,Detector,Probability density function,Complex normal distribution,Bayes estimator,Mathematics
Journal
Volume
Issue
ISSN
83
6
Signal Processing
Citations 
PageRank 
References 
13
1.85
1
Authors
4
Name
Order
Citations
PageRank
Emmanuelle Jay1174.90
Jean Philippe Ovarlez219025.11
David Declercq3131.85
Patrick Duvaut47627.15