Due to the growing complexity of ground battlefield environment, the radar target recognition method has received intensive attention. Radar high resolution range profile (HRRP) has been widely used for practical target recognition system for its easy acquisition and low storage requirement. For radar HRRP recognition, two aspects are of great importance to improve the performance, i.e. discrimination for outlier and classification for inner. To tackle these issues, a novel target recognition method is designed, denoted by multiple support vectors method. First, a treble correlate support vector model is constructed to segment the feature space into two regions according to the density of feature vectors, then the description and classification hyper plane for each region are obtained. Based on the support vector framework, the computation complexity can be reduced significantly for practical radar HRRP recognition. Finally, the experiment based on the measured data verifies the excellent performance of the proposed method.