Radar signal classification based on auto-correlation function and directed graphical model

This paper proposes a new radar signal classification algorithm based on auto-correlation function (ACF) and directed graphical model (DGM). The ACFs of analytic radar signals are calculated to magnify the discrimination of signals of different categories. A simple de-noising approach is introduced to purify the ACFs. Four features are extracted from the purified ACF. A DGM is used to represent the joint probability distribution of the four features along with the category and to classify unknown radar signals. Simulation results show the effectiveness of this classification algorithm.