Target Recognition of Radar HRRP Using Manifold Learning with Feature Weighting

High range resolution profile (HRRP) contains important target structure signatures and is easy to be acquired, which makes HRRP target recognition keep drawing great attention from the radar target recognition community. Firstly, data are preprocessed and the features are weighted with their sensitive-values. Then, using feature extraction method based on manifold learning to reduce the feature dimensions. At last, a minimum distance classifier is designed to recognize targets. The simulation experiment results demonstrate that the proposed method is an effective method which achieves good recognition performance and robustness.