HRRP feature extraction and recognition method of radar ground target using convolutional neural network

High resolution range profile(HRRP) is an important feature of radar target. It can be used to classify and recognize target. As for the attitude sensibility, the HRRP of target will change dramatically within a small angle. Since the convolutional neural network(CNN) is good tool to abstract the HRRP features from the original input data, and these features have good generalization ability to represent the target HRRP. Aiming at this issue, an approach is proposed to realize radar ground target HRRP features extraction and recognition based on convolutional neural network. The target scattering center features are reorganized into a 2-D feature map. Then a CNN is constructed to recognize the target based on the feature map of the target. The computation result based on MSTAR database shows the performance of the proposed approach.