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JCP
2008

Radar Signal Detection In Non-Gaussian Noise Using RBF Neural Network

13 years 11 months ago
Radar Signal Detection In Non-Gaussian Noise Using RBF Neural Network
In this paper, we suggest a neural network signal detector using radial basis function (RBF) network. We employ this RBF Neural detector to detect the presence or absence of a known signal corrupted by different Gaussian, non-Gaussian and impulsive noise components. In case of non-Gaussian noise, experimental results show that RBF network signal detector has significant improvement in performance characteristics. Detection capability is better than to those obtained with multilayer perceptrons (BP) and optimum matched filter (MF) detector. This signal detector is also tested on the simulated signals impacted by impulsive noise produced by atmospheric events and short lived echoes from meteor trains. Tested Results show, improved detection capability to impulsive noise compare to BP signal detector. It also show better performance as a function of signal-tonoise ratio compared to BP and MF.
Dilip Gopichand Khairnar, S. N. Merchant, Uday B.
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2008
Where JCP
Authors Dilip Gopichand Khairnar, S. N. Merchant, Uday B. Desai
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