A Support Vector Regression (SVR) based on semi-parametric Radar Cross Section (RCS) fluctuation statistical model is proposed. The idea is to simplify the most used correction factor of semi-parametric model by using only support vectors instead of full sampling represen-tation. Simulation results demonstrate that the proposed model can efficiently express the RCS distribution, and dramatically decrease the samplings number for constructing formulation.%提出一种基于支持向量回归机(Support Vector Regression,SVR)的半参数化雷达散射截面(Radar Cross Section,RCS)起伏统计模型。该模型通过利用 SVR 将常规半参数化模型中修正因子全样本表出简化为支持向量表出,从而达到提高模型执行效率的目的。仿真实验结果表明,该模型可以有效表达 RCS 样本分布,且显著降低模型表出所需样本量。
展开▼
