Acoustic identification of buried underwater unexploded ordnance using a numerically trained classifier (L)

Abstract

Using a finite element-based structural acoustics code, simulations were carried out for the acoustic scattering from an unexploded ordnance rocket buried in the sediment under 3 m of water. The simulation treated 90 rocket burial angles in steps of 2°. The simulations were used to train a generative relevance vector machine (RVM) algorithm for identifying rockets buried at unknown angles in an actual water/sediment environment. The trained RVM algorithm was successfully tested on scattering measurements made in a sediment pool facility for six buried targets including the rocket at 90°, 120°, and 150°, a boulder, a cinderblock, and a cinderblock rolled 45° about its long axis.