• 学报（中文） •

### 基于支持向量机的雷达电子支援措施系统点迹-航迹关联算法

1. 1. 上海交通大学 自动化系， 上海 200240； 2. 中航工业雷华电子技术研究所， 江苏 无锡 214063
• 发布日期:2019-10-11
• 通讯作者: 李建勋，男，教授，博士生导师，电话(Tel.): 021-34204305；E-mail：lijx@sjtu.edu.cn.
• 作者简介:王江卓（1993-），男，河北省石家庄市人，硕士生，主要研究方向为模式识别与智能系统.
• 基金资助:
装备预研领域基金项目(61404130103)，2015 中航工业产学研专项，国家自然科学基金 (61673265)，国家重点基础研究发展计划(6133190302)资助项目

### Dot-Track Association Algorithm for Radar Electronic Support Measurement Systems Based on Support Vector Machine

WANG Jiangzhuo 1,XU Wencong 1,LI Jianxun 1,HE Fengshou 2,CAO Lanying 2,MIAO Lifeng 2

1. 1. Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China; 2. AVIC Leihua Electronic Technology Research Institute, Wuxi 214063, Jiangsu, China
• Published:2019-10-11

Abstract: Probabilistic data association is an important issue in multi-source information fusion algorithms. The data association problem based on radar and electronic support measurement (ESM) sensors is mainly discussed in this paper. As the azimuthal data of radar and ESM sensors have approximately the same distribution, the discriminant function can be obtained through the analysis of ESM data, and the corresponding decision rules can be used to associate the dots and tracks. The association issue can be essentially regarded as a pattern recognition problem. In this paper, considering the good performance of support vector machine(SVM) in pattern classification, we establish a dotting and tracking association model for radar ESM systems based on SVM algorithm. We train the SVM model with ESM data, and classify the radar data to acquire association result. Finally, the simulation results show that the association accuracy can be effectively improved compared with the classical multiple hypothesis tracking algorithm.