Modulation Recognition Method of Non-cooperation Underwater Acoustic Communication Signals Using Principal ComponentAnalysis

doi:10.3969/j.issn.1000-1093.2016.09.017

Abstract

Abstract: The modulation classification of the non-cooperation underwater acoustic communication signals is extremely challenging due to channel transmission characteristics and low signal-to-noise ratio. The principal component analysis (PCA) is used to analyze the power spectra and square spectrum features of signals, which is capable of extracting the principal components associated with different modulated signals as input vector, thus reducing the feature dimension and suppressing the influence of noise. An artificial neural network (ANN) classifier is proposed for modulation recognition. The experimental modulation classification results obtained from field signals in 4 different underwater acoustic channels show that the proposed modulation recognition method has good classification performance.

Key words: acoustics, underwater acoustic digital modulated signal, spectrum feature, modulation recognition, principal component analysis, ANN classifier

CLC Number:

TN929.3

JIANG Wei-hua, TONG Feng, WANG Bin, LIU Shi-gang. Modulation Recognition Method of Non-cooperation Underwater Acoustic Communication Signals Using Principal ComponentAnalysis[J]. Acta Armamentarii, 2016, 37(9): 1670-1676.

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