Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)

Vector Deviation for Recognition of Radar Target Intention

Authors
Dong YAN, De-cun BIAN, Jin-chang ZHAO, Shao-qing NIU
Corresponding Author
Dong YAN
Available Online December 2016.
DOI
10.2991/cnct-16.2017.50How to use a DOI?
Keywords
Target Intention; Eigenvector; Standard Vector; Vector Deviation.
Abstract

Radar data were used to develop judgement rules for target intention by analysis for known targets. For the eigenvector with corresponding dimension established by the known target, the standard vector determined by the air target vector with the known intention was adopted as the judging criteria. Matlab software was used to calculate the vector deviation between target and standard vectors to define intention clusters, and predict target intention. The assessment of suspicious target intention using vector deviation was validated to be rapid and precise.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-301-2
ISSN
2352-538X
DOI
10.2991/cnct-16.2017.50How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Dong YAN
AU  - De-cun BIAN
AU  - Jin-chang ZHAO
AU  - Shao-qing NIU
PY  - 2016/12
DA  - 2016/12
TI  - Vector Deviation for Recognition of Radar Target Intention
BT  - Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)
PB  - Atlantis Press
SP  - 357
EP  - 368
SN  - 2352-538X
UR  - https://doi.org/10.2991/cnct-16.2017.50
DO  - 10.2991/cnct-16.2017.50
ID  - YAN2016/12
ER  -