ON SPATIAL UNCERTAINTY IN A SURFACE LONG BASELINE POSITIONING SYSTEM

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.