引用本文:徐西蒙,杨任农,于洋,等.基于运动分解和H-SVM的空战目标机动识别[J].控制与决策,2020,35(5):1265-1272
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基于运动分解和H-SVM的空战目标机动识别
徐西蒙1,杨任农1,于洋2,张涛1
(1. 空军工程大学空管领航学院,西安710051;2. 中国人民解放军95810部队,北京100076)
摘要:
目标机动识别是空战态势感知中的关键问题.针对现有识别方法主观因素较多、模型复杂、难以满足实时性和识别准确率不够高等问题,提出一种基于运动分解和层次支持向量机(hierarchical support vector machine, H-SVM)的机动识别方法.利用$v\text{-
关键词:  空战  机动识别  H-SVM  运动分解  ACMI
DOI:10.13195/j.kzyjc.2018.1210
分类号:V249
基金项目:
Target maneuver recognition in air combat based on motion decomposition and H-SVM
XU Xi-meng1,YANG Ren-nong1,YU Yang2,ZHANG Tao1
(1. Air Traffic Control and Navigation College,Air Force Engineering University, Xián710051,China;2. Unit 95810 of the PLA,Beijing100076,China)
Abstract:
Target maneuver recognition is a key problem in air combat situation awareness. Aiming at the problems of the existing recognition methods such as more subjective factors, complicated models, difficult to meet the real-time performance and low recognition accuracy, a maneuver recognition method based on motion decomposition and hierarchical support vector machine(H-SVM) is proposed. The H-SVM multi-classifier is constructed by using the $v\text{-
Key words:  air combat  maneuver recognition  H-SVM  motion decomposition  ACMI

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