Cart (Loading....) | Create Account
Close category search window
 

Generalized CFAR Property and UMP Invariance for Adaptive Signal Detection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
De Maio, A. ; DIBET, Universit?? degli Studi di Napoli ??Federico II??, Napoli, Italy

In this paper we consider adaptive detection of a signal embedded in additive disturbance whose multivariate distribution belongs to a very general class, including many statistical models commonly adopted for radar disturbance. We introduce the concept of generalized Constant False Alarm Rate (CFAR) and show that a class of receivers sharing some invariances complies with the quoted property. Then, we devise the Generalized Likelihood Ratio Test (GLRT) and prove that, under some mild technical conditions, it coincides with that obtained under the Gaussian assumption for the observations. We also deal with the existence of the Uniformly Most Powerful Invariant (UMPI) detector either using the Wijsman theorem or directly computing the maximal invariant Likelihood Ratio (LR). At the analysis stage, we focus on a compound matrix variate model for the disturbance component, which is a natural generalization of the Spherically Invariant Random Vector (SIRV). In this context, we assess the performance of some well known invariant decision rules also in comparison with the Most Powerful Invariant (MPI) detector. The results highlight that some among the analyzed receivers exhibit a performance level very close to the MPI test.

Published in:

Signal Processing, IEEE Transactions on  (Volume:61 ,  Issue: 8 )

Date of Publication:

April15, 2013

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.