Abstract
This paper introduces a passive acoustic method for detecting and tracking marine vessels via Time Difference of Arrival (TDoA) estimates collected by an array of synchronized Intelligent Buoys (SIBs). A 24-hour deployment recorded a passing tanker's acoustic signature, which we processed with band-pass filtering and sliding-window cross-correlation, to extract robust TDoA time series. We implemented a nonlinear Gauss-Newton estimator to reconstruct the vessel's trajectory. Position tracking fails, given the geometric configuration of the SIBs with regard to the vessel's trajectory but we suggest a possible solution to overcome this problem using synthesized data inspired on the experiment.

Abstract
Planar surfaces are commonly found in man-made underwater environments and can be employed to support underwater SLAM. This work focuses on 3D plane extraction, building on two-dimensional acoustic scans collected from an imaging sonar. The novel contribution of our algorithm exploits the sonar's wider beamwidth and ability to collect secondary echoes from these structures to extract a three-dimensional surface from the acquired acoustic image. Building on a Hough Transform-based algorithm adapted to polar-based acoustic imagery, line feature detection supports plane representation segmentation. An inverse sensor model is subsequently employed to estimate additional plane parameters: inclination, length, and height. Experimental assessment in a confined controlled environment is introduced, validating the accuracy of the algorithm. Additional results from a dam shaft scenario are also presented to assess the potential of the developed tool.