Systems Engineering and Electronics ›› 2023, Vol. 45 ›› Issue (2): 481-489.doi: 10.12305/j.issn.1001-506X.2023.02.19

• Systems Engineering • Previous Articles    

Automatic analysis and mining algorithm of air target formation

Qiuping XU, Jiejing ZHOU, Hai JI, Ming GENG, Yuanyuan LE   

  1. The 28th Research Institute of China Electronics Technology Group Corporation, Nanjing 210007, China
  • Received:2021-08-07 Online:2023-01-13 Published:2023-02-04
  • Contact: Qiuping XU

Abstract:

In response to the needs of battlefield situation data analysis and rule knowledge mining, based on the accumulated historical activity information of battlefield targets, the deep-level correlation characteristics between the targets are analyzed. And the Prim algorithm and template matching ideas are used to construct models for target relationship judgment, target formation automatic extraction, and formation feature matching and recognition. Furthermore, a fast and practical algorithm for automatic analysis and mining of air target formation is proposed. The feasibility and effectiveness of the proposed algorithm model are verified by several simulation cases. The proposed algorithm can quickly and effectively mine associated target formations from the massive historical activity data and provide the target association credibility, and can effectively identify the formation characteristics, such as the association relationship between the targets and the type of the formation. In addition, the proposed algorithm has a small amount of calculation and is easy to be implemented in engineering.

Key words: target formation, association relationship, formation type, Prim algorithm

CLC Number: 

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