Title :
MIMO radar detection in compound-Gaussian clutter with inverse Gaussian texture
Author :
Sijia Chen ; Guolong Cui ; Lingjiang Kong ; Jianyu Yang
Author_Institution :
Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
The compound-Gaussian (CG) distribution with the inverse Gaussian (IG) texture is represented as the IG-CG distribution and validated to provide the better fit with the recorded clutter data than the traditional K distribution as well as the complex multivariate t distribution. In this paper, the adaptive detector of multiple-input multiple-output (MIMO) radar is firstly proposed in terms of the generalized likelihood ratio test (GLRT) criterion against the IG-CG clutter, and the constant false alarm rate (CFAR) property is evaluated. Numerical simulations illustrate the effectiveness of the proposed detector.
Keywords :
Gaussian distribution; MIMO radar; maximum likelihood detection; radar clutter; radar detection; CFAR property; GLRT criterion; IG texture; IG-CG clutter; IG-CG distribution; K distribution; MIMO radar detection; clutter data; complex multivariate t distribution; compound-Gaussian clutter; compound-Gaussian distribution; constant false alarm rate; generalized likelihood ratio test; inverse Gaussian texture; multiple-input multiple-output radar; Clutter; Covariance matrices; Detectors; MIMO radar; Radar cross-sections; Thyristors;
Conference_Titel :
Radar Conference, 2014 IEEE
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-1-4799-2034-1
DOI :
10.1109/RADAR.2014.6875587