Experimental demonstration of cognitive radar for target localization under strong interference

Abstract

One of the major objectives of cognitive radar is to form a dynamic closed feedback loop to adapt the spectrum of transmit waveforms to avoid certain interference. In this paper, we build an automatic closed-loop cognitive radar to support experimental study of the radar system in real-world situations. Convex optimization is applied to jointly design sounding waveforms and the matched filters with spectral power suppressed in arbitrary bands and with low correlation sidelobes as well. Target localization is demonstrated under strong interferences. Experimental results are provided to evaluate the performance of the cognitive radar system.