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Proceedings Paper

A linear stochastic process and a genetic algorithm for ship trajectory modeling
Author(s): Melita Hadzagic; Hannah Michalska
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Paper Abstract

The goal of this paper is to compare the performance of an algorithm employing the Integrated Ornstein- Uhlenbeck process with a genetic algorithm based method for ship track modeling. The positional measurements, received at irregular time intervals are assumed to have heteroscedastic and correlated errors and available in batches. The quality of the produced tracks is assessed using several simulated scenarios and evaluated statistically. The results of this performance evaluation are useful as they facilitate selecting the appropriate approach to data processing in maritime surveillance applications, hence contribute to increased maritime domain awareness.

Paper Details

Date Published: 28 April 2010
PDF: 11 pages
Proc. SPIE 7697, Signal Processing, Sensor Fusion, and Target Recognition XIX, 76970V (28 April 2010); doi: 10.1117/12.849350
Show Author Affiliations
Melita Hadzagic, McGill Univ. (Canada)
Hannah Michalska, McGill Univ. (Canada)


Published in SPIE Proceedings Vol. 7697:
Signal Processing, Sensor Fusion, and Target Recognition XIX
Ivan Kadar, Editor(s)

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