A Study on Radar Target Detection Based on Deep Neural Networks
Target detection is one of the most important radar applications widely used in practice. Target detection can be regarded as a kind of classification, which distinguishes whether the signal undertested consists of an echo from a target (target present) or just corresponds to the noise (target absent) The deep neural network (DNN) is a popular topic for classification and has successfully been applied in different fields of science. Recently, many researchers have proposed DNNs for radar applications. In this article, we analyze a possible application of DNN for target detection in radar, DNN based detectors are designed, and the performance of the detector is demonstrated by comparison with traditional target detectors.
IEEE Sensors Letters