A robust neural network scheme for constant false alarm rate processing for target detection in clutter environment

The authors present a novel neural network-based CFAR detection scheme (referred to as NN-CFAR scheme) that offers a robust performance in the face of loss of reference cells. This scheme employs a multilayer feedforward neural network trained by the error backpropagation approach using the optimal detector as the teacher.