A new multitarget tracking approach based on a non-iterative fuzzy clustering means algorithm

In this paper, a new multitarget tracking approach is proposed. In the proposed approach, a non-iterative fuzzy clustering means algorithm is used to generate the association measures between the received measurements and the targets. Measurements-to-tracks associations are computed jointly across a...

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Published in:2015 IEEE Aerospace Conference pp. 1 - 10
Main Author: Aziz, Ashraf M.
Format: Conference Proceeding Journal Article
Language:English
Published: IEEE 01.03.2015
Subjects:
Aircraft components
Algorithms
Clustering
Correlation
Fuzzy
Fuzzy logic
Fuzzy set theory
Logic gates
Noise
Noise measurement
Target tracking
Tracking
Weight measurement
ISBN:9781479953790, 1479953792
ISSN:1095-323X
Online Access:Get full text
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Abstract In this paper, a new multitarget tracking approach is proposed. In the proposed approach, a non-iterative fuzzy clustering means algorithm is used to generate the association measures between the received measurements and the targets. Measurements-to-tracks associations are computed jointly across all targets and all validated measurements using the non- iterative fuzzy clustering means algorithm. For a given target, the validated measurement that has the maximum fuzzy association weight is used for updating the state of the target. The performance of the proposed approach is evaluated and compared to that of the standard nearest-neighbor association and conventional fuzzy logic data association approaches. The results show that the proposed tracking approach achieves better performance compared to the standard tracking approach and the conventional fuzzy tracking approaches.
AbstractList In this paper, a new multitarget tracking approach is proposed. In the proposed approach, a non-iterative fuzzy clustering means algorithm is used to generate the association measures between the received measurements and the targets. Measurements-to-tracks associations are computed jointly across all targets and all validated measurements using the non- iterative fuzzy clustering means algorithm. For a given target, the validated measurement that has the maximum fuzzy association weight is used for updating the state of the target. The performance of the proposed approach is evaluated and compared to that of the standard nearest-neighbor association and conventional fuzzy logic data association approaches. The results show that the proposed tracking approach achieves better performance compared to the standard tracking approach and the conventional fuzzy tracking approaches.
Author Aziz, Ashraf M.
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Snippet In this paper, a new multitarget tracking approach is proposed. In the proposed approach, a non-iterative fuzzy clustering means algorithm is used to generate...
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SubjectTerms Aircraft components
Algorithms
Clustering
Correlation
Fuzzy
Fuzzy logic
Fuzzy set theory
Logic gates
Noise
Noise measurement
Target tracking
Tracking
Weight measurement
Title A new multitarget tracking approach based on a non-iterative fuzzy clustering means algorithm
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