Abstract:The echo signal of a high-range-resolution radar(HRR) contains much information about target. By using this information and feature extraction method fully and properly, an efficient target recognition can be executed. A novel approach for radar target recognition is proposed in this paper. This approach explores canonical analysis on a matrix formed by the image vectors of training targets in different aspect angles. One image vector contains both the amplitudes and relative phases of the range profile of a target. A subspace is obtained from this analysis. Projection of an image vector into this subspace forms subimage. The subimages of a training target in different aspect angles are averaged into library feature vector for this target. Using the subimage of an unknown target as feature vector and minimum distance rule for target recognition, experiments on simulated data are done.