Statistical processing techniques for detecting DRFM repeat-jam radar signals

Electronic countermeasure (ECM) techniques against RF missile systems are enhanced by using radio frequency digital memory (DRFM) to preserve the radar signal for subsequent re-transmission with deceptive modulation in order to confuse the missiles tracking radar. The aim of the study was to investigate whether such radar platforms could use statistical signal processing to differentiate between real and false target returns. It is shown that enhanced linear discriminant analysis (LDA) and also artificial neural network (ANN) processing can discriminate down to three bit DRFM resolution depending on received jammer-to-noise ratio.