针对非均衡样本的雷达字提取算法  

A Radar Word Extraction Algorithm for Unbalanced Samples

作　　者：高天昊 曲卫 王鹏达 董尧尧 姜浩浩 朱霸坤 GAO Tianhao;QU Wei;WANG Pengda;DONG Yaoyao;JIANG Haohao;ZHU Bakun(Space Engineering University Graduate School,Beijing 101000 China;Space Engineering UniversityDepartment of Electronic and Optical Engineering,Beijing 101000 China)

机构地区：[1]航天工程大学研究生院,北京101000 [2]航天工程大学电子与光学工程系,北京101000

出　　处：《电光与控制》2022年第11期38-43,共6页Electronics Optics & Control

基　　金：国防科技创新特区项目基金(19-H863-01-ZT-003-003-15)。

摘　　要：雷达字作为构成雷达短语的基元,其提取效果的好坏将直接影响后续雷达行为辨识的可信度。针对侦收数据不均衡情况下的雷达字提取问题,提出一种基于K-means算法改进的K-OPTICS雷达字提取算法。通过构建虚拟聚类中心和簇合并的方法,使其在各种样本不均衡的仿真场景下仍能取得91.22%以上的提取准确率,较传统算法具有更好的参数不敏感性。Radar words are the primitives of radar phrase and the extraction effect of radar words will directly affect the confidence of subsequent radar behaviour recognition.A solution is proposed for the radar word extraction problem in the case of unbalanced detection and acquisition data i.e.an improved K-OPTICS radar word extraction algorithm based on K-means.By constructing virtual clustering centres and cluster merging it achieves an extraction accuracy higher than 91.22%under various unbalanced sample simulation scenarios and has better parameter insensitivity than the traditional algorithm does.

关 键 词：雷达字 多功能相控阵雷达 非均衡样本 K-OPTICS 

分 类 号：TN958[电子电信—信号与信息处理]