Boosting Estimation Accuracy of Low-Cost Monopulse Receiver Via Deep Neural Network

In this paper, a low-cost monopulse receiver is presented to achieve high accuracy of angular estimation by applying deep neural network. The low-cost receiver is composed of a 4 - element patch array, a planar comparator network, and a down conversion module. Different from other signal processing methods, a deep neural network is developed for proposed low-cost monopulse receiver, which can map the misaligned target angular positions in the measurement to the actual physical location under detection.