Aiming at the problem of exoticism of the intraclass dispersion matrix and sensitivity to isolated points in narrowband radar target data reduction of discriminant locality preserving projections(DLPP)in narrow-band radar target data,a narrow-band radar air targets classification method based on robust margin DLPP(RMDLPP)is proposed.Firstly,the Euclidean distance of the two sample points is correlated with the homogeneous sample mean value when calculating the distance between samples.Then,a certain number of boundary sample points are selected for processing and the DLPP objective function is optimized for dimensionality reduction.Finally,a high-performance classifier is used to distinguish the dimensionality reduction data and achieve the classification of aerial targets.Comparative experiments on X-band air-to-air alert radar measurements show that the proposed method has better classification accuracy and robustness to isolated points.
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