"Efficient Sequential Monte Carlo Bayesian geoacoustic inversion of large volume dataset from Malta Plateau" by Eric Mandolesi (University of Victoria, Canada)
DIAS seminar will continue September 1st at 16.00 with a talk by Eric Mandolesi, from the University of Victoria, Canada. He will present his latest results on the inversion of ocean acoustic data using Bayesian Monte Carlo techniques.
1st September 2017
Seabed geoacoustic properties play a crucial role in shallow-water sonar applications, including the detection of unexploded ordnance. Our goal is improved efficiency of Bayesian seabed parameter and uncertainty estimation for large data volumes. While Bayesian uncertainty estimation provides important information for sonar applications, the approach is computationally expensive which limits utility for large surveys. This work considers the efficiency of a particle filter to quantify information content of multiple data sets along the survey track by considering results from previous data along the track to inform the importance sampling at the current point. Efficiency is improved by tempering the likelihood function of particle subsets and including exchange moves (parallel tempering), and by adapting the proposal distribution along the Markov-chains. Particularly, perturbations are proposed in principal-component space. The developed filter has been applied to seabed reflectivity data recorded using an autonomous underwater vehicle (AUV) on the Malta Plateau. The inversion provides rich seabed information in a reasonable time framework. The survey reveals a low-velocity (<1500 m/s) wedge with low attenuation of initially 1.2-m thickness, thinning towards the Sicilian coast and disappearing after 8 km. An erosional, high-velocity boundary is increasingly buried by low-velocity material towards the coast.
Location and time: The seminar will be held at 16.00 Friday Sept. 1st in the Dublin Institute for Advanced Studies Geophysics Library, 5 Merrion Square, Dublin 2.