Copyright © 2008 The Institute of Electronics, Information and Communication Engineers
Regular Section -- Papers -- Sensing |
Distributed Fuzzy CFAR Detection for Weibull Clutter
1 The authors are with the Department of Electrical Engineering, Yazd University, Yazd, Iran. E-mail: mrtaban{at}yazduni.ac.ir, 2 The author is with the Sharif University of Technology, Tehran, Iran.
In Distributed detection systems, restricting the output of the local decision to one bit certainly implies a substantial information loss. In this paper, we consider the fuzzy detection, which uses a function called membership function for mapping the observation space of each local detector to a value between 0 and 1, indicating the degree of assurance about presence or absence of a signal. In this case, we examine the problem of distributed Maximum Likelihood (ML) and Order Statistic (OS) constant false alarm rate (CFAR) detections using fuzzy fusion rules such as "Algebraic Product"(AP), "Algebraic Sum"(AS), "Union"(Un) and "Intersection"(IS) in the fusion centre. For the Weibull clutter, the expression of the membership function based on the ML or OS CFAR processors in the local detectors is also obtained. For comparison, we consider a binary distributed detector, which uses the Maximum Likelihood and Algebraic Product (MLAP) or Order Statistic and Algebraic Product (OSAP) CFAR processors as the local detectors. In homogenous and non homogenous situations, multiple targets or clutter edge, the performances of the fuzzy and binary distributed detectors are analyzed and compared. The simulation results indicate the superior and robust performance of the distributed systems using fuzzy detection in the homogenous and non homogenous situations.
Key Words: distributed detection, OS-CFAR, ML-CFAR, fuzzy, Weibull
Manuscript received April 4, 2007. Manuscript revised August 28, 2007.
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