Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (9): 70-75.doi: 10.11896/jsjkx.210800203

• Database & Big Data & Data Science • Previous Articles     Next Articles

Aerial Target Grouping Method Based on Feature Similarity Clustering

CHAI Hui-min1,2, ZHANG Yong2, FANG Min1   

  1. 1 School of Computer Science and Technology,Xidian University,Xi'an 710071,China
    2 Science and Technology on Electro-Optical Information Security Control Laboratory,Tianjin 300308,China
  • Received:2021-08-23 Revised:2022-03-11 Online:2022-09-15 Published:2022-09-09
  • About author:CHAI Hui-min,born in 1976,Ph.D,associate professor.Her main research interests include information fusion and situation awareness.
  • Supported by:
    Defense Pre-Research Foundation of China(6142107190106).

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Abstract: In order to solve the problems that the number of clusters needs to be given and the sensitivity to the initial positions of the cluster centers while clustering algorithm is utilized for target grouping,a novel aerial target grouping method based on feature similarity clustering is proposed.Firstly,the similarity between targets is calculated and the similarity matrix is constructed.Then,the connected branches of the similarity matrix are calculated to obtained the group center structure and the isolated target points are detected.The number of group center structures is the number of clusters.Finally,the targets which are not belonging to the group center structure and the isolated points are clustered into the closest group center structure.It makes the clustering process no longer depend too much on the initialization of the cluster centers.Experimental results show that the proposed methodcan correctly identify the group center structure and detect the isolated points.Furthermore,its the clustering accuracy is higherthan that of other four clustering algorithms.

Key words: Aerial target grouping, Clustering algorithm, Target similarity, Group center structure

CLC Number: 

  • TP391.9
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