Geoacoustic parameter estimation through iteratively particle filtering of solitary data set

In Bayesian inversion schemes, geoacoustic parameter values and associated uncertainties normally are obtained through sampling approaches, e.g., Metropolis-Hastings (M-H) sampling. This paper presents an attempt to solve this problem through applying a particle filter (PF) to solitary data input as collected in the Yellow Sea, China, 2002. In the experiment, a 38-g explosive charge was used as a broadband source that detonated at an approximate depth of 7 m. The recording system is a moored vertical line array composed of 30 pressure sensors. Comparison between the performances of PF and M-H sampling is first made with numerical tests based on the Yellow Sea environmental model, and then are applied to the real atsea data. Results from both synthetic and real data processing demonstrate the PF is an efficient approach in geoacoustic parameters estimation.