By Topic

Radar detection based on compound-gaussian model with inverse gamma texture

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

2 Author(s)
Shang, X. ; Dept. of Space Microwave Remote Sensing Syst., Chinese Acad. of Sci., Beijing, China ; Song, H.

The coherent radar detection against a background of compound-Gaussian clutter with inverse gamma texture is studied and three detectors: One-step generalised likelihood ratio test (1S-GLRT), maximum a posteriori GLRT (MAP-GLRT) and two-step GLRT (2S-GLRT) are proposed. The detectors have the same structure with their test statistics and modified thresholds, respectively, related to the scale and the shape parameters of the texture, which can also be formulated in a matched filter (MF) form. Subsequently, the performance assessments are given by their probability of detection and probability of false alarm. The authors find that the probability of false alarm is dependent on the shape parameter, meaning the detectors have no CFAR property. When the shape parameter and the number of the integrated radar pulses satisfy certain condition, it has no relation with the shape parameter and then the detectors have CFAR property. Finally, simulation results show that: (i) 1S-GLRT and MAP-GLRT have the same performance for fixed probability of false alarm and 2S-GLRT bears slightly bad performance; (ii) the performance of 1S-GLRT is much closer to the adaptive coherence estimator (ACE) and is better than that of the Kelly GLRT and (iii) the 1S-GLRT is robust when parameter estimation errors exist.

Published in:

Radar, Sonar & Navigation, IET  (Volume:5 ,  Issue: 3 )