线性预测编码系数分类雷达反射截面积目标的方法及实现  

Method and Realization of RCS Target Classification by LPC Coeffient

作　　者：倪风岳 于长海 NI Feng-yue;YU Chang-hai(Jiuquan Satellite Launch Center,Jiuquan 732750,China)

机构地区：[1]中国酒泉卫星发射中心,甘肃酒泉732750

出　　处：《光学与光电技术》2020年第2期42-46,共5页Optics & Optoelectronic Technology

摘　　要：空间中不同的目标具有不同的物理与几何特性,雷达反射截面积(RCS)是空间目标的重要特性之一,利用RCS对雷达观测目标进行区分是雷达数据处理的重要手段。利用线性预测编码(LPC)技术对RCS测量数据进行处理,计算RCS的LPC系数,以该系数作为特征向量,对目标进行二分类识别率基本可以达到80%~90%以上,三分类识别可以达到50%~80%以上,可以有效提高雷达跟踪目标的自动分类,实现高效半自动或自动跟踪。Different targets in space have different physical and geometry characteristics.RCS(Radar Cross-Section)is one of the most important characteristics of targets,so it is a very important method to classify targets based on RCS data.LPC(Linear Predictive Coding)is used to process RCS data in order to obtain LPC coefficients of them.Then the LPC coefficients are used as feature vectors for targets classification and recognition.In this way,the classification rate can be up to 80%~90%when classifying two targets.And the classification rate can be up to 50%~80%when classifying three targets.This method can effectively improve the radar automatic classification capability so as to track targets semi-automatically and automatically.

关 键 词：线性预测编码 雷达反射截面积 支撑向量机 特征向量 自动跟踪 

分 类 号：E91[军事] TN953[电子电信—信号与信息处理]