Convolutional Neural Networks for Radar Detection

The use of convolutional neural networks (CNN’s) for radar detection is evaluated. The detector includes a time-frequency block that has been implemented by the Wigner-Ville distribution and the Short-Time Fourier Transform to test the suitability of both techniques. The CNN detectors are compared with the classic multilayer perceptron and with several traditional non-neural detectors. Preliminary results are shown using non-correlated and correlated Rayleigh-envelope clutter.