Dense false-target jamming Suppression Method Based on the Scene Cognition Network

Abstract

Recognition and suppression of dense false-target jamming has been a hotspot in research of radar anti-jamming technique. This essay proposes a method to suppress the dense false-target jamming according to scene cognition. Model of scene cognition network is obtained off-line through training real and imaginary data after pulse compression of echo data. Real targets and jamming will be recognized intelligently with the full-trained scene cognition network. Dense false-target jamming is suppressed with multistage spectral peak detection and spectrum removing in the recognized jamming area. Finally, jamming suppression results are imported to the scene cognition network again to evaluate the effect of jamming suppression. The results of experiments of simulated data and actual data prove that proposed method can effectively suppress the dense false-target jamming and detect the real targets. Our method is relatively valuable in engineering application.