Estimation of cylinder orientation using autonomous underwater vehicle mapping of bistatic scattered fields

Abstract

When an aspect-dependent target is insonified by an acoustic source, distinct features are produced in the resulting bistatic scattered field. These features were exploited in a process for estimating target aspect angles that was demonstrated on a real-world data set using models produced using simulation data. Bistatic scattering data was collected during an experiment in November 2014 in Massachusetts Bay using a ship-based acoustic source producing 7-9kHz LFM chirps and a steel pipe target. The true target orientation was unknown, as the target was dropped from the ship with no rotation control. The Autonomous Underwater Vehicle (AUV) Unicorn, fitted with a 16-element nose array and data acquisition payload, was deployed in broadside data collection behaviors around the target, and the ship was moved to create two target aspects. Scattering data was collected for each target aspect angle. A Support Vector Machine (SVM) regression model was trained using simulated scattering bistatic field data from the OASES-SCATT simulation package. This model was used to estimate the target aspect angles using the real data collected by the AUV during the experiment. The aspect angle estimates were consistent with experimental observations of relative source positioning based on ship position.