Radar transmitter classification using a non-stationary signal classifier

This paper presents a classification method which discriminates between two radar transmitters based on the received pulses. A simple radar transmitter model is presented to which a non-stationary signal classifier is applied. The classifier is a support vector machine which is applied to the radar pulse's time-frequency representation. The time-frequency representation is refined using particle swarm optimization to increase the classification accuracy. The classification accuracy is tested in an additive white Gaussian noise channel. An acceptable classification accuracy is reported for component tolerances as small as 2% on the transmitter's modulator. © 2009 IEEE.