By Topic

Use of perturbation methods in the problem of radar detection against a K-clutter background

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 $31
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

3 Author(s)
De Angelis, R. ; Dipartimento di Matematica, Rome Univ., Italy ; Farina, A. ; Zirilli, F.

The paper studies a model of K-distributed clutter in a radar detection problem. The clutter is modelled with a multidimensional Gaussian probability density function where the variance values are represented by a set of independent random variables distributed with a function. The detection of an a prior known target against the considered K-clutter is studied using the likelihood ratio test. To evaluate the probabilities of false alarm (Pfa) and detection (Pd), we propose, as an alternative to the usual Monte Carlo simulation, a procedure that, resorting to analytical and numerical methods, approximates Pfa and Pd by a power series expansion in terms of a suitable parameter of the model. The numerical work is greatly reduced in the region where the expansion holds. In fact, the high-dimensional integrals involved in the power series expansion are reduced to products of low-dimensional ones. A numerical comparison with the standard Monte Carlo computation has been performed on a test case. The approach used here can be adapted to K-models with correlated Gamma variables

Published in:

Radar, Sonar and Navigation, IEE Proceedings -  (Volume:142 ,  Issue: 5 )