Feature extraction of radar emitter signals based on symbolic time series analysis

Abstract

An useful approach is proposed for intra-pulse feature extraction of radar emitter signals based on symbolic time series analysis(STSA). Embedding time-delay and modified Shannon entropy are used as two-dimensional feature vector to sort the interleaving radar signals. The time-delay feature can determine the length of symbol series. The entropy feature can quantitatively reveal deterministic information and complexity of radar intra-pulse modulation signals. In order to show the effectiveness and feasibility of the introduced approach, the experimental results indicate that the features of seven typical radar emitter signals extracted by STSA have good characteristics of clustering and strong stability when SNR varies from 0dB to 30dB and the method of STSA for finding and quantifying information is computationally efficient, robust to noise and easy to use in engineering implementation and application.