Performance of Distributed CFAR Processors in Pearson Distributed Clutter
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Research Article Performance of Distributed CFAR Processors in Pearson Distributed Clutter Zoubeida Messali and Faouzi Soltani D´epartement d’Electronique, Facult´e des Sciences de l’Ing´enieur, Universit´e de Constantine, Constantine 25000, Algeria Received 30 November 2005; Revised 17 July 2006; Accepted 13 August 2006 Recommended by Douglas Williams This paper deals with the distributed constant false alarm rate (CFAR) radar detection of targets embedded in heavy-tailed Pearson distributed clutter. In particular, we extend the results obtained for the cell averaging (CA), order statistics (OS), and censored mean level CMLD CFAR processors operating in positive alpha-stable (P&S) random variables to more general situations, specifically to the presence of interfering targets and distributed CFAR detectors. The receiver operating characteristics of the greatest of (GO) and the smallest of (SO) CFAR processors are also determined. The performance characteristics of distributed systems are presented and compared in both homogeneous and in presence of interfering targets. We demonstrate, via simulation results, that the distributed systems when the clutter is modelled as positive alpha-stable distribution offer robustness properties against multiple target situations especially when using the “OR” fusion rule. Copyright © 2007 Z. Messali and F. Soltani. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
In radar detection, the goal is to automatically detect a target in a nonstationary noise and clutter while maintaining a constant probability of false alarm. Classical detection using a matched filter receiver and a fixed threshold is no longer applicable due to the nonstationary nature of the background noise. Indeed, a small increase in the total noise power results in a corresponding increase of several orders of magnitude in the probability of false alarm. Therefore, adaptive threshold techniques are needed to maintain a constant false alarm rate. Hence, CFAR detectors have been designed to set the threshold adaptively according to local information on the background noise. More specifically, CFAR detectors estimate the characteristics of the noise by processing a window of reference cells surrounding the cell under test. The CA approach is such an adaptive procedure. However, the CA detector has a severely degraded performance in clutter edge and interfering targets echoes [1, 2]. Rohling modified the common CA-CFAR technique by replacing the arithmetic averaging estimator of the clutter power by a new module based on order statistics (OS) [3]. The OS-CFAR procedure protects against nonhomogeneous situations caused by clutter edges and interfering targets (which is of interest in this paper). Target detectability and robustness against
interfering targets can also be enhanced using distributed detection [4, 5]. However, the design o
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