Feature Extraction of Radar Emitter Signal Based on Wavelet Packet and EMD

Abstract

AbstractTo research the problem of radar emitter signal (RES) recognition, and to further enhance emitter signal recognition capacity of the electronic warfare equipment, the empirical mode decomposition (EMD) theory and wavelet packet (WP) are introduced into feature extraction of radar emitter signal. A new feature extraction method of radar emitter signal is proposed based on wavelet packet and empirical mode decomposition theory. First, it uses wavelet packet to finish decomposition, de-noising and reconstruction of the RES. Then it will obtain the intrinsic mode function (IMF) through EMD method, which can incarnate the characteristics of RES. The energy of each IMF are calculated and normalized, which would be regarded as the feature vector. Finally it realizes the classification of radar emitter signal by constructing BP neural network classifier. Experiment results show that the feature extraction method based on wavelet packet and empirical mode decomposition is an effective feature extraction method for RES, which can achieve satisfying correct recognition rate in a larger signal to noise ratio. It would have certain reference value in follow-up in-depth study.KeywordsOriginal SignalEmpirical Mode DecompositionWavelet PacketFeature Extraction MethodRadar SignalThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.