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.
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