A Novel Methodology for Target Classification Based on Dempster-Shafer Theory

被引：0
|
作者：
Turhan, Hasan Ihsan [1 ]
Demirekler, Mubeccel [1 ]
Gunay, Melih [2 ]
机构：
[1] Middle East Tech Univ, Ankara, Turkey
[2] ASELSAN Inc, Ankara, Turkey
来源：
BELIEF FUNCTIONS: THEORY AND APPLICATIONS (BELIEF 2014) | 2014年 / 8764卷
关键词：
Dempster-Shafer Theory; Belief Functions; Basic Probability (Mass) Assignment; Dempster-Shafer Reasoning; Target Tracking; Decision Making; Target Classification; FUZZY C-MEANS; BELIEF FUNCTIONS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, classification of air vehicles according to their types is studied. Demspter-Shafer theory is utilized for this purpose. The target tracker data is used for obtaining the probability masses by comparing it with the prior information. Prior information is modeled as the probability density function of the features used for classification. The prior information models the selected features as Gaussian mixtures while the tracker data models the same features as non-parametric density. This new methodology is tested on real data.
引用
收藏
页码：393 / 402
页数：10
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