Performance analysis of GLRT-based adaptive detector for distributed targets in compound-Gaussian clutter

Authors:
Xiaofei Shuai;Lingjiang Kong;Jianyu Yang
Affiliations:
School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China;School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China;School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
Venue:
Signal Processing
Year:
2010

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Abstract

The problem of adaptive detection for spatially distributed targets in compound-Gaussian clutter is studied. We first derive the optimum NP detector and suboptimum two-step GLRT detector. For the two-step detection strategy, we also introduce three covariance matrix estimation strategies and evaluate their CFAR properties and complexity issues. Next, the numerical results are presented by means of Monte Carlo simulation strategy. In particular, the simulation results highlight that the performance loss due to adaptively estimating the texture is negligible, and that the loss due to adaptively estimating covariance matrix largely depends on the estimation algorithm, the number of the secondary data vectors and the number of the scatterers.