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 from component tolerances as small as 2% on the transmitter's modulator.
Reference:
Du Plessis, MC and Olivier, JC. 2009. Radar transmitter classification using non-stationary signal classifier.
Du Plessis, M., & Olivier, J. (2009). Radar transmitter classification using non-stationary signal classifier. Institute of Electrical and Electronic Engineering (IEEE). http://hdl.handle.net/10204/3878
Du Plessis, MC, and JC Olivier. "Radar transmitter classification using non-stationary signal classifier." (2009): http://hdl.handle.net/10204/3878
Du Plessis M, Olivier J, Radar transmitter classification using non-stationary signal classifier; Institute of Electrical and Electronic Engineering (IEEE); 2009. http://hdl.handle.net/10204/3878 .
Copyright: 2009 Institute of Electrical and Electronics Engineering (IEEE). Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE
