Low Sidelobes Patterns for Pulse Doppler Radar Detection using Artificial Neural Networks

In this paper Artificial Neural Networks (ANNs) are being considered to obtain low sidelobe pattern for Binary Barker codes and thereby to improve the performance of pulse Doppler radar. Various types of ANN networks like MLP (Multi-Layer Perception), RNN (Recursive Neural Networks), RBF (Radial Basis Function) and RRBF (Recurrent Radial Basis Function) are being considered. The Performance Metrics used are PSLR (Peak Sidelobe Ratio), ISLR (Integrated Sidelobe Ratio) and SSR (Signal-to-Sidelobe Ratio). The code performance in terms of Range and Doppler Resolution is also presented in the paper.