On spatial uncertainty in a surface long baseline positioning system
Résumé
This paper describes a general method for estimating the probability distribution of an acoustic source resulting from noisy measurements in a surface long baseline (SLBL) positioning system. Compared with Monte Carlo simulations this method calculates the mean and covariance at a reduced computational cost, due to a deterministic sampling strategy. Hence, it can easily be checked if a SLBL configuration is well suited to a particular positioning scenario.
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