Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)

Application of the Particle Filter in Manuver Target Turn Tracking Algorithm

Authors
Zhenda Lei
Corresponding Author
Zhenda Lei
Available Online December 2016.
DOI
10.2991/iceeecs-16.2016.74How to use a DOI?
Keywords
Non-linear; Non-Gausss;Particle Filtering; Uncertainties;
Abstract

The non-linear target-tracking method has been extensive researched to solve turn maneuver target. Particle filter is suitable for any non-linear, non-Gaussian system that could be represented with many kinds of turn manuver,Good Methods are needed in Manuer Tracking. Particle filter is demonstated that it has better performance when compared with the Extended kalman filter to target tracking. when used in tracking algorithm, the new filter yields improved performance in the case of model uncertainties. The simulation results indicate that manure tracking algorithm can maintain track under severe correlates maneuvers when using Particle filter which is better than Extended kalman filter.

Copyright
© 2016, 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 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-265-7
ISSN
2352-538X
DOI
10.2991/iceeecs-16.2016.74How to use a DOI?
Copyright
© 2016, 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  - Zhenda Lei
PY  - 2016/12
DA  - 2016/12
TI  - Application of the Particle Filter in Manuver Target Turn Tracking Algorithm
BT  - Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
PB  - Atlantis Press
SP  - 357
EP  - 360
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.74
DO  - 10.2991/iceeecs-16.2016.74
ID  - Lei2016/12
ER  -