摘要
提出了灰关联分析与模糊推理相结合的方法,称为GCA-FDM。GCA-FDM主要用于低时间分辨率的战术机动目标之间的关联。选取航天监测信息中相对稳定的目标属性特征作为基本的关联参量,计算目标间的关联度,以此作为目标关联的判决依据。同时,综合考虑当前战场各方面信息,利用模糊推理方法,对灰关联结果进行修正,从而能够得到更好的结果。GCA-FDM对目标样本数量没有太大的要求,具有广泛的实用性,弥补了经典关联算法在低时间分辨率目标关联中的不足。通过一个应用案例详细说明了GCA-FDM算法的操作过程。
A gray correlation analysis and fuzzy discursion method （GCA-FDM） is put forward in this paper. It can resolve the tactics movement target association problem based on low time resolving power. The steady target attribute in remote sensing information is chosen as the basic correlation parameter. Targets are distinguished by computing correlation degree. It can obtain the better result by considering current all kinds of the battlefield information and using the fuzzy discursion method. GCA-FDM algorithm has not higher requirement on target samples, so it can be widely used. In target association fields, this algorithm makes up the disadvantage of classic association algorithm with low time resolving power. An application example is given to illustrate the usage of GCA-FDM algorithm.
出处
《华东理工大学学报（自然科学版）》
CAS
CSCD
北大核心
2007年第5期712-715,共4页
Journal of East China University of Science and Technology
关键词
航天遥感
灰关联
模糊推理
目标关联
战术应用
remote sensing
gray correlation
fuzzy discursion
target association
tactical application
作者简介
闫子豪（1976-），男，河北邢台人，硕士，主要研究方向为战场目标识别，E—mail：zihaoyan@126．com
