Distributed CA-CFAR and OS-CFAR Detectors Mentored by Biogeography Based Optimization Tool
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Date
2019
Authors
Journal Title
Journal ISSN
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Publisher
Université de M'sila
Abstract
In this paper, distributed constant false alarm
rate (CFAR) detection in homogeneous and heterogeneous
Gaussian clutter using Biogeography Based Optimization
(BBO) method is analyzed. For independent and dependent
signals with known and unknown power, optimal thresholds
of local detectors are computed simultaneously according to a
preselected fusion rule. Based on the Neyman-Pearson type
test, CFAR detection comparisons obtained by the genetic
algorithm (GA) and the BBO tool are conducted. Simulation
results show that this new scheme in some cases performs
better than the GA method described in the open literature in
terms of achieving fixed probabilities of false alarm and
higher probabilities of detection
Description
Keywords
BBO, distributed CFAR detection, CACFAR, OS-CFAR, fusion rule