• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2022, Vol. 44 ›› Issue (01): 159-164.

• 人工智能与数据挖掘 • 上一篇    下一篇

基于MRF模型的飞机飞行动作识别划分算法

颜廷龙1,李瑛2,王凤芹2   

  1. (1.海军航空大学岸防兵学院,山东 烟台 264001;2.海军航空大学航空基础学院,山东 烟台 264001)

  • 收稿日期:2020-08-06 修回日期:2020-11-18 接受日期:2022-01-25 出版日期:2022-01-25 发布日期:2022-01-13

Recognition  and division of aircraft flight action based on MRF model

YAN Ting-long1,LI Ying2,WANG Feng-qin2   

  1. (1.College of Coastal Defense,Naval Aviation University,Yantai 264001;

    2.College of Basic Sciences for Aviation,Naval Aviation University,Yantai 264001,China)
  • Received:2020-08-06 Revised:2020-11-18 Accepted:2022-01-25 Online:2022-01-25 Published:2022-01-13

摘要: 军用飞机飞行动作具有较强的随机性和模糊性,为实现针对军用飞机飞行动作的识别和划分,提出了一种基于马尔可夫随机场MRF模型的飞行动作识别划分算法,可以在没有标定的情况下,将飞行数据段分割聚类,实现飞行动作的识别和划分。仿真实验表明,相比于传统的飞行动作识别算法,基于MRF模型的飞行动作识别划分算法且有更高的识别率。

关键词: 马尔可夫随机场, 动作识别, 多元时间序列, 聚类

Abstract: Military aircraft flight action have strong randomness and ambiguity. In order to realize the recognition and division of military aircraft flight action, a Markov Random Field (MRF) based recognition and division algorithm is proposed. The flight data segment is divided and clustered to realize the recognition and division of flight actions. Simulation experiments show that, compared with traditional flight action  recognition algorithms, the flight action recognition algorithm based on the MRF model has a higher recognition rate.



Key words: Markov random field, action recognition, multivariate time series, clustering