AR-model-based adaptive detection of range-spread 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:
2011

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Abstract

In this paper, we consider the problem of adaptive detection for range-spread targets with known Doppler and unknown complex amplitude in compound Gaussian clutter. The speckle component of the clutter is modeled as an autoregressive (AR) process. By using the generalized likelihood ratio test (GLRT) approach, we will first estimate the AR parameters and the unknown complex amplitude, and then propose an adaptive AR-based GLR detector. The performance assessments are presented too. The computer simulations show that the proposed detector, without a priori information of the covariance matrix, has the same asymptotical performances as the two-step GLR-based detector with known covariance matrix.