Automatic Classification of LFM Signals for Radar Emitter Recognition Using Wavelet Decomposition and LVQ Classifier

E. Świercz Faculty of Electrical Engineering, Białystok University of Technology, Wiejska 45D, 15-351 Białystok, Poland

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The paper presents a novel approach, based on the wavelet decomposition and the learning vector quantisation algorithm, to automatic classification of signals with linear frequency modulation, generated by radar emitters. The goal of radar transmitter classification is to determine the particular transmitter, from which a signal originated, using only the just received waveform. To categorise a current linear frequency modulation signal to the particular transmitter, the discrete wavelet decomposition of the received signal is accomplished in order to get a representative set of features with good classification properties. The learning vector quantisation algorithm with a previously defined set of features as an input of the learning vector quantisation neural net is proposed as the intelligent classification algorithm, which combines competitive learning with supervision. After the learning process, the learning vector quantisation algorithm is ready to perform: the classification process for different data than data used in the learning stage. Simulation results show the high classification accuracy for experimentally chosen wavelets and suggested architecture of the learning vector quantisation classifier.

DOI: 10.12693/APhysPolA.119.488 PACS numbers: 84.40.Ua, 84.35.+i