To improve the performance of radar emitter recognition under low signal-to-noise ratio

a method that extracts features from ambiguity function with derivative constraint on smoothing is proposed.A mathematical model to obtain the max energy angle based on rounding function and coordinate transformation is set

greatly reducing processing complexity.An algorithm picking the waveform of max energy slice is also presented referring to derivative constraint on smoothing.It depends on none specific signal and noise models.The algorithm is transferred into Second-order Cone Programming (SOCP) for solving and it weakens the influence caused by noise upon ambiguity function waveform features to a great extent.According to the validity index

values of the regularization parameter in objective function and the norm parameter in symmetrical Holder coefficient are determined.Finally

fuzzy c-means clustering is implemented for classification and recognition of feature vectors extracted from emitter signals.Simulation results indicate that the method presented in the paper gains higher correct recognition rate.