A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm

A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm

Target grouping can divide battlefield targets into battle space groups. In this way, the target grouping reduces the difficulty of situation assessment and increases the efficiency of decision. In order to solve the target grouping, a target grouping method based on Manifold-CFSFDP algorithm is pro...

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Format: Article
Language:zho
Published: The Northwestern Polytechnical University 2018-12-01
Series:Xibei Gongye Daxue Xuebao
Subjects:
situation assessment
target grouping
manifold
cfsfdp
dynamic grouping
Online Access:https://www.jnwpu.org/articles/jnwpu/pdf/2018/06/jnwpu2018366p1121.pdf
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spelling doaj-2c045e2a0c2144b68014ee468e51632d2021-05-02T20:24:29ZzhoThe Northwestern Polytechnical UniversityXibei Gongye Daxue Xuebao1000-27582609-71252018-12-013661121112810.1051/jnwpu/20183661121jnwpu2018366p1121A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm0123School of Automation, Northwestern Polytechnical UniversitySchool of Automation, Northwestern Polytechnical UniversitySchool of Automation, Northwestern Polytechnical UniversityAVIC Xi'an Flight Automatic Control Research InstituteTarget grouping can divide battlefield targets into battle space groups. In this way, the target grouping reduces the difficulty of situation assessment and increases the efficiency of decision. In order to solve the target grouping, a target grouping method based on Manifold-CFSFDP algorithm is proposed. This method turns target grouping into dataset clustering. After calculating the manifold which measures the similarity of targets, it searches the clustering centers and classifies the other data points by CFSFDP based on manifold. The simulation experiment for artificial and UCI datasets proves that M-CFSFDP is more effective than CFSFDP. The correctness and feasibility of M-CFSFDP are also shown by static and dynamic grouping of battlefield targets.https://www.jnwpu.org/articles/jnwpu/pdf/2018/06/jnwpu2018366p1121.pdfsituation assessmenttarget groupingmanifoldcfsfdpdynamic grouping
collection DOAJ
language zho
format Article
sources DOAJ
title A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm
spellingShingle A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm
Xibei Gongye Daxue Xuebao
situation assessment
target grouping
manifold
cfsfdp
dynamic grouping
title_short A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm
title_full A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm
title_fullStr A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm
title_full_unstemmed A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm
title_sort battlefield target grouping method based on m-cfsfdp algorithm
publisher The Northwestern Polytechnical University
series Xibei Gongye Daxue Xuebao
issn 1000-2758
2609-7125
publishDate 2018-12-01
description Target grouping can divide battlefield targets into battle space groups. In this way, the target grouping reduces the difficulty of situation assessment and increases the efficiency of decision. In order to solve the target grouping, a target grouping method based on Manifold-CFSFDP algorithm is proposed. This method turns target grouping into dataset clustering. After calculating the manifold which measures the similarity of targets, it searches the clustering centers and classifies the other data points by CFSFDP based on manifold. The simulation experiment for artificial and UCI datasets proves that M-CFSFDP is more effective than CFSFDP. The correctness and feasibility of M-CFSFDP are also shown by static and dynamic grouping of battlefield targets.
topic situation assessment
target grouping
manifold
cfsfdp
dynamic grouping
url https://www.jnwpu.org/articles/jnwpu/pdf/2018/06/jnwpu2018366p1121.pdf
_version_ 1721487630580842496

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