基于加权广义匹配滤波联合SVDD的FOD检测算法  

FOD Detection Algorithm Based on WGMF and SVDD

作　　者：卢宁[1] LU Ning(College of Computer Engineering Technical,Guangdong Polytechnic of Science and Technology,Zhuhai Guangdong 519090,China)

机构地区：[1]广东科学技术职业学院计算机工程技术学院,广东珠海519090

出　　处：《现代雷达》2023年第5期112-119,共8页Modern Radar

基　　金：广东省普通高校特色创新项目(2019GKTSCX029)。

摘　　要：利用毫米波雷达进行机场跑道异物(FOD)检测是当前民航安全领域的一种流行解决方案。由于非均匀杂波的存在,传统基于恒虚警率的检测方法存在虚警率过高、检测性能较差的问题。文中提出一种加权广义匹配滤波(WGMF)联合支撑向量数据描述(SVDD)的FOD检测方法。首先,利用WGMF对雷达记录的FOD回波数据进行预处理,实现杂波抑制的同时降低虚警概率;然后,对回波数据提取双谱特征,实现数据由原始回波域向差异性更大的特征域的转变;最后,利用SVDD一类分类器实现FOD检测。在某机场跑道真实场景开展验证实验,结果表明所提方法能够有效降低虚警概率,提升检测性能。Using millimeter wave radar to detect foreign object debris(FOD)in airport runway is a popular solution in the field of civil aviation safety.Due to the existence of non⁃uniform clutter,the traditional detection method based on constant false alarm rate has the problems of high false alarm rate and poor detection performance.A weighted generalized matched filtering(WGMF)com⁃bined with support vector data description(SVDD)method is proposed.Firstly,WGFM is used to preprocess the radar recorded FOD echo data to suppress clutter and reduce the false alarm probability.Then,bispectral features are extracted from the echo data to realize the transformation of the data from the original echo domain to the feature domain.Finally,FOD detection is realized by SVDD classifier.The experimental results show that the proposed method can effectively reduce the false alarm probability and im⁃prove the detection performance.

关 键 词：毫米波雷达 机场跑道异物 加权广义匹配滤波 模型优化 一类分类器 

分 类 号：TN957.51[电子电信—信号与信息处理]