摘要
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。
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.
出处
《电子信息对抗技术》
2015年第4期47-50,共4页
Electronic Information Warfare Technology
关键词
雷达散射截面
起伏统计模型
回波模拟
支持向量回归机
radar cross section
fluctuation statistical model
radar target echo simulation
sup-port vector regression machine
