Abstract
A radar signal recognition can be accomplished by exploiting the particular features of modulation presented in a radar signal observed in presence of noise. These modulation features are the result of slight radar component variations and acts as an individual signature of a radar. The paper describes a radar signal classification algorithm based on using the Wigner-Ville Distribution (WVD), noise reduction procedure with using a two-dimensional filter and the RBF neural network probability density function estimator which extracts the features vector used for the final radar signal classification. The numerical simulation results for the P4-coded signals are presented.
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