基于多输出最小二乘支持向量回归模型的测向方法  

A Direction-finding Method Based on MLSSVR Model

作　　者：黄凯 尤明懿[1,2] 叶云霞 江斌[1,2] 陆安南 HUANG Kai;YOU Ming-yi;YE Yun-xia;JIANG Bin;LU An-nan(Science and Technology on Communication Information Security Control Laboratory,Jiaxing Zhejiang 314033,China;No.36 Research Institute of CETC,Jiaxing Zhejiang 314033,China)

机构地区：[1]通信信息控制和安全技术重点实验室,浙江嘉兴314033 [2]中国电子科技集团公司第三十六研究所,浙江嘉兴314033

出　　处：《通信对抗》2021年第3期27-31,共5页Communication Countermeasures

摘　　要：相位干涉仪是一种常用的测向系统,具有较高的测向精度。当测向系统存在综合误差时,各类校正算法大部分都需要基于天线阵几何位置的预假设,而利用机器学习的方法是数据驱动型方法,可以不依赖于这些假设。因此介绍一种基于多输出最小二乘支持向量回归模型的干涉仪测向方法,该方法的运用包括模型训练数据构建、训练并构建模型、来波方向估计等三个步骤。最后通过数值仿真来验证该算法的有效性,当测向系统存在综合误差时,该算法可有效提高测向精度。The interferometer is a widely used direction-finding system with high precision.When there are comprehensive disturbances in the direction-finding system,some scholars have proposed corresponding correction algorithms,but most of them require hypothesis based on the geometric position of the array.The method of using machine learning that has attracted much attention recently is data-driven,which can be independent of these assumptions.So we propose a direction-finding method for an interferometer direction-finding system by using multi-output least squares support vector regression(MLSSVR)model.The application of this method includes:the construction of MLSSVR model training data,training and construction of MLSSVR model,the estimation of direction of arrival.Finally,the method is verified through numerical simulation.When there are comprehensive deviations in the system,the direction-finding accuracy can be effectively improved.

关 键 词：干涉仪 测向 综合误差 多输出最小二乘支持向量回归 

分 类 号：TN971[电子电信—信号与信息处理]