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A novel fractional autocorrelation based feature extraction approach for radar emitter signals

An effective approach to extract the features of ambiguity function main ridge (AFMR) slice of radar emitter signals is proposed, in which fractional autocorrelation is used to search the AFMR, and moment method is adopted to describe the distribution characteristics of AFMR slice. The results of theoretical analysis and simulation experiments show that, the extracted characteristics vector of AFMR slice clearly expresses the differences of waveform in different signals, and it has strong compactness within clusters and good ability to resist noise. So it can be served as the optional parameter of deinterleaving for complicated radar emitter signals.