Automatic Target Recognition Using Recurrent Neural Networks

Abstract

Automatic target recognition (ATR) using recurrent neural networks (RNN) is being proposed in this work. When electromagnetic waves from radar illuminate the targets, surface currents are produced which results in scattering of the incident energy. The scattered signal in the direction of radar is received as the radar signature of the target. The radar cross section (RCS) is an important feature extracted from the radar signature which is used in this work for target identification. The RCS values for each set of azimuth and elevation angles for a mono-static configuration serves the purpose of the dataset for the recurrent neural network (RNN)/long short-term memory (LSTM) model. The classification accuracy of 93 percent was achieved using the RNN/LSTM model.