箔条弹RCS测量数据异常值的检验与剔除算法研究  

Outliers Detection and Removing in RCS Measurement Data of Chaff Bomb

作　　者：韩伟[1] 张鸿喜[1] 

机构地区：[1]91404部队93分队,秦皇岛066001

出　　处：《系统仿真技术》2016年第4期318-321,328,共5页System Simulation Technology

摘　　要：传统的异常值剔除方法主要是针对静态测量数据,箔条弹RCS(雷达反射截面积)特性测量属于动态测量,由于动态系统测量中的数据是不断变化的,因此不能沿用静态测量中的数据异常值的剔除方法和判别准则。针对这个问题,提出了利用绝对均值法和基于邻近去最值均值滤波检测方法两种方法,对箔条弹RCS测量数据中的异常值进行剔除,并给出了实际算例。研究结果可为箔条弹RCS测量试验中数据处理及其他动态测量异常数据剔除提供方法借鉴。Traditional outlier removing method is aiming at static measurement data, measurement of the chaff bomb RCS characteristics is dynamic. Since dynamical measurement data is constantly changing, the outliers detection and removing method for static measurement cannot be adoped anymore. To address this problem,absolute mean value method and the average value filtering method based on the adjacent are proposed to remove the outliers in the chaff bomb RCS data, and some examples are siven. The main results of this study can provide solutions for the the chaff bomb RCS data process and outliers removing of the related dynamical measurement

关 键 词：动态测量 异常值 均值滤波 雷达截面积 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]