Automatic HRR target recognition based on Prony model wavelet and probability neural network

Abstract

An automatic high range resolution (HRR) target recognition algorithm is detailed and tested on a data set of five different aircraft. A super-resolution downrange profile of radar returns of HRR is obtained using the Prony model. Target features are extracted by the wavelet transform. The features consist of two parts: one reflects the detailed structure of the targets, the other shows the outline of the targets. A probabilistic neural network (PNN) with a simple data fusion technique is applied for target classification.