Automatic modulation classification of radar signals using the Rihaczek distribution and hough transform

It is an important work to classify the modulation type of the intercepted radar signal for an electronic intelligence (ELINT) receiver in a non-cooperative environment. The authors use the Rihaczek distribution (RD) and the Hough transform (HT) to concentrate the energy in time-frequency plane and derive two new characteristic features, namely the ratio of the minimum to the maximum of the HT and the peak number of the HT of the real part of the RD, to improve the probabilities of successful recognition (PSRs) to recognise the classical low probability of intercept (LPI) radar signals. The first feature is especially suitable for the linear frequency modulation (LFM), whereas the second one is specifically designed for frequency shift keying (FSK). The choice of thresholds and the effects of signal parameters are analysed. Simulations show that the PSRs can reach 90% when the signal-to-noise ratio (SNR) is above -4 dB. The proposed algorithm is better than the previous algorithms by just using ambiguity function.