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Automatic identification of the digital modulation type of a signal has found applications in many areas, including electronic warfare, surveillance and threat analysis. This paper studies the use of wavelet transform to distinguish QAM signal, PSK signal and FSK signal. The approach is to use the wavelet transform to extract the transient characteristics in a digital modulation signal, and apply the distinct pattern in wavelet transform domain for simple identification. The relevant statistics for optimum threshold selection are derived under the condition that the input noise is additive white Gaussian. The performance of the identification scheme is investigated through simulations. When the CNR is greater than 5 dB, the percentage of correct identification is about 97% with 50 observation symbols.
Hong et al. (Mon,) studied this question.