一种历史特征辅助的模糊数据关联算法  

Fuzzy data association algorithm assisted by historical features

作　　者：韩卓茜 王锋 陈沛 李卓伦 HAN Zhuoxi;WANG Feng;CHEN Pei;LI Zhuolun(School of Data and Target Engineering,PLA Strategic Support Force Information Engineering University,Zhengzhou 450001,China;Unit 61827 of PLA,Shanghai 200000,China;School of Information System Engineering,PLA Strategic Support Force Information Engineering University,Zhengzhou 450001,China)

机构地区：[1]中国人民解放军战略支援部队信息工程大学数据与目标工程学院,河南郑州450001 [2]中国人民解放军61827部队,上海200000 [3]中国人民解放军战略支援部队信息工程大学信息系统工程学院,河南郑州450001

出　　处：《西安电子科技大学学报》2021年第2期92-98,108,共8页Journal of Xidian University

基　　金：国家自然科学基金青年项目(61501513)。

摘　　要：针对观测数据存在强模糊性和不确定性问题,提出了一种基于高分辨一维距离像历史特征辅助的模糊数据关联算法。首先,针对高分辨一维距离像的姿态、幅度以及时移敏感性问题,对其提取得到敏感性低的特征;然后,使用航迹起始的特征构建初始特征样本库及历史时刻的特征构建历史特征样本库,并实时更新特征样本库;采用区间熵权法确定特征权重,计算量测与目标的模糊隶属度,构建模糊矩阵;最后,基于最大模糊隶属度原则实现量测与目标的关联。实验结果表明,在目标的机动和非机动场景下,这种算法的关联性能均优于模糊关联算法,并且随着杂波密集程度的增大,两个算法的关联性能均逐渐降低,但所提算法的关联性能更好。Aiming at the problem of strong ambiguity and uncertainty in the observed data,the author proposes a fuzzy data association algorithm based on the historical features of high-resolution one-dimensional range profile.First,for the high-resolution one-dimensional range profile's attitude,amplitude,and time-shift sensitivity,feature extraction is performed to obtain low-sensitivity features.Then,the features of the track initiation are used to construct the initial feature sample database;the features of the historical moment are utilized to construct the historical feature sample database,and the feature sample database is updated in real time.The feature weight is obtained by the interval entropy weight method and the fuzzy membership of the measurement,and the target is calculated to construct a fuzzy matrix.Finally,fuzzy data association is completed based on the principle of maximum fuzzy membership.Experimental results show that,in both the maneuvering and non-maneuvering scenarios of the target,the association performance of the proposed algorithm is better than that of the fuzzy data association algorithm.And with the increase in the clutter density,the association performance of the two algorithms is gradually decreased,but the association performance of the proposed algorithm becomes better.

关 键 词：高分辨一维距离像 历史特征 特征提取 特征辅助 区间熵权法 模糊数据关联 关联 

分 类 号：TN953[电子电信—信号与信息处理]