雷达科学与技术2013，Vol.11Issue(4)：363-367,374,6.DOI:10.3969/j.issn.1672-2337.2013.04.005
基于灰关联度和距离的特征关联算法研究
A Novel Feature Association Algorithm Based on Grey Correlation Grade and Distance Measure
摘要
Abstract
Feature association is a key link of passive multi-sensor tracking.A novel algorithm based on grey correlation grade and distance measurement is proposed to solve the problem of the corresponding fuzzy of measurement and its origination,which is caused by the measurement error produced in the process of multi-sensor system measuring the characteristic parameter of multi-emitter.The grey correlation grade and distance measure between the characteristic vectors are accounted to cluster the characteristic vectors of high similarity measurement,which eliminates the corresponding fuzzy problem successfully.Data-base of multiemitter is simulated,the performance of different similarity measurement and the correlation correct rate are discussed in different noise environments.The validity of association is proved.The simulation results show the correlation correct rate of grey correlation grade is higher than the distance measurement,but consumes longer time.关键词
多传感器系统/特征关联/灰关联度/距离度量Key words
multi-sensor system/ feature association/ grey correlation grade/ distance measurement分类
信息技术与安全科学引用本文复制引用
关欣,孙祥威,何友..基于灰关联度和距离的特征关联算法研究[J].雷达科学与技术,2013,11(4):363-367,374,6.基金项目
新世纪优秀人才支持计划(No.NCET-11-0872) （No.NCET-11-0872）
