舰船电子工程2019，Vol.39Issue(10)：196-199,4.DOI:10.3969/j.issn.1672-9730.2019.10.044
弹道数据野值灰色自适应检测与修正
Grey Adaptive Detection and Correction of Outliers in Ballistic Data
摘要
Abstract
The identification and correction of outliers in ballistic measurement data is an important link to improve the accura?cy and quality of data processing. In this paper,the grey theory is introduced into the outlier processing of measurement data. The grey metabolic model is used for rolling prediction of measurement data. The outliers are identified according to the adaptive thresh?old. The outliers are corrected by using new information to realize the detection and correction of outliers in ballistic data. The simu?lation results show that the proposed method can achieve a comprehensive recognition rate of more than 92% for randomly generated outliers,and the minimum outlier detection ratio is less than 4.5%,which meets the requirements of general engineering practice.关键词
弹道数据/野值/灰色/自适应/检测与修正Key words
ballistic data/outliers/grey/adaptive/detection and correction分类
军事科技引用本文复制引用
杨军,张东..弹道数据野值灰色自适应检测与修正[J].舰船电子工程,2019,39(10):196-199,4.基金项目
国家自然科学基金项目"弹道导弹动态总体多响应多因素飞行试验的一体化设计"(编号:61573367)资助. （编号:61573367）
