Semi-parametric statistic model via support vector regression for radar target HRRP recognition

In radar target high-resolution range profile (HRRP) recognition, the target aspect sensitivity problem is mainly solved by angular domain division and template modeling for each angular sector. Semi-parametric statistic model has both advantages of parametric statistic model and non-parametric statistic model, and is proved to be a valid HRRP template. However, when the number of HRRP samples in an angular sector is large, the efficiency might be low because of the non-parametric correction factor used in semi-parametric statistic model. To solve this problem, a semi-parametric statistic model via support vector regression (SVR) is proposed in this paper. By SVR, the idea is to reduce all the samples to only support vectors to formulate the non-parametric correction factor. Experiment results using 5 aircraft HRRP dataset demonstrate the efficiency of the proposed model.