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Digital Library of the
European Council for Modelling and Simulation |
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Title: |
Application
of Computational Intelligence to Target Tracking |
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Authors: |
Lars Nolle |
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Published in:
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ECMS
2007 Proceedings Edited
by: Ivan Zelinka, Zuzana Oplatkova, Alessandra Orsoni ISBN:
978-0-9553018-2-7 Doi: 10.7148/2007 21st European
Conference on Modelling and Simulation, Prague, June
4-6, 2007 |
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Citation
format: |
Nolle, L. (2007). Application of
Computational Intelligence to Target Tracking. ECMS 2007 Proceedings edited
by: I. Zelinka, Z. Oplatkova,
A. Orsoni (pp. 289-293).
European Council for Modeling and Simulation. doi:10.7148/2007-0289. |
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DOI: |
http://dx.doi.org/10.7148/2007-0289 |
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Abstract: |
In the oceanic context, the aim of Target Motion Analysis
(TMA) is to estimate the state, i.e. location, bearing and velocity, of a
sound-emitting object. These estimates are based on a series of passive
measures of both the angle and the distance between an observer and the
source of sound, which is called the target. These measurements are corrupted
by noise and false readings, which are perceived as outliers. Usually, sequences of measurements are taken and
statistical methods, like the Least Squares method or the Annealing
M-Estimator, are applied to estimate the target's state by minimising the residual in range and bearing for a series
of measurements. In this
project, an ACO-Estimator, a novel hybrid optimisation
algorithm based on Computational Intelligence, has been developed and applied
to the TMA problem and its effectiveness was compared with standard
estimators. It was shown that the new algorithm outperforms conventional
estimators by successfully removing outliers from the measurements. |
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