Abstract
Two types of distributed constant false alarm rate (CFAR) detection using binary and fuzzy weighting functions in fusion center are developed. In the two types of distributed detectors, it was assumed that the clutter parameters at the local sensors are unknown and each local detector performs CFAR processing based on ML and OS CFAR processors before transmitting data to the fusion center. At the fusion center, received data is weighted either by a binary or a fuzzy weighting functions and combined according to deterministic rules, constructing global test statistics. Moreover, for the Weibull clutter, the expression of the weighting functions, based on ML and OS CFAR processors in local detectors, is obtained. In the binary type, we analyzed various distributed detection schemes based on maximum, minimum, and summation rules in fusion center. In the fuzzy type, we consider the various distributed detectors based on algebraic product, algebraic sum, probabilistic OR, and Lukasiewicz t-conorm fuzzy rules in fusion center. The performance of the two types of distributed detectors is analyzed and compared in the homogenous and nonhomogenous situations, multiple targets, or clutter edge. The simulation results indicate the superiority and robust performance of fuzzy type in homogenous and non homogenous situations.
Highlights
E essential problem in radar detection is to determine whether or not a target is present in a special region based on single sensor detection schemes or distributed sensor detection schemes
Each local sensor computes the value of membership functions to the false alarm space from the sample of the reference cells and transmits it to the fusion center where the nal decision is made based on fuzzy fusion rules
We analyzed various distributed detection scheme based on maximum likelihood (ML) (OS) constant false alarm rate (CFAR) processor in local detectors and maximum, minimum, and summation rules in fusion center. e employment of the binary weighting functions, in the binary type, certainly causes signi cant loss of information in the fusion center
Summary
E essential problem in radar detection is to determine whether or not a target is present in a special region based on single sensor detection schemes or distributed sensor detection schemes. Each local sensor computes the value of membership functions to the false alarm space from the sample of the reference cells and transmits it to the fusion center where the nal decision is made based on fuzzy fusion rules. It was shown in [12] that algebraic product fuzzy fusion rules provide a better performance than those of the OR or AND under the condition of the Gaussian clutter.
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