Ship detection and tracking from single ocean-bottom seismic and hydroacoustic stations.

We report in this study how ocean-bottom seismometers (OBS) can be used as passive sonars to automatically detect, localize, and track moving acoustic sources at the ocean surface. We developed single-station methods based on direction of arrival and on multi-path interference measurements capable of handling continuous erratic signals emitted by ships. Based on a Bayesian mathematical framework, we developed an azimuthal detector and a radial detector and combined them into a fully automatic tracker.

Detection of envelope modulation and direction of arrival estimation of multiple noise sources with an acoustic vector sensor.

The Detection of Envelope Modulation on Noise (DEMON) is an algorithm that is commonly applied to hydrophone data for the detection and classification of underwater noise produced by a ship. This algorithm utilizes modulation analysis to determine the frequencies that modulate the broadband cavitation noise produced by marine vessel propellers. In this paper, a DEMON demodulator for acoustic vector sensors (AVSs) that are directional hydrophones capable of acquiring both the acoustic pressure and the components of the particle velocity vector is defined.

Heterogeneous integrated dataset for Maritime Intelligence, surveillance, and reconnaissance.

Facing an ever-increasing amount of traffic at sea, many research centres, international organisations, and industrials have favoured and developed sensors together with detection techniques for the monitoring, analysis, and visualisation of sea movements. The Automatic Identification System (AIS) is one of the electronic systems that enable ships to broadcast their position and nominative information via radio communication. In addition to these systems, the understanding of maritime activities and their impact on the environment also requires contextual maritime data capturing additional features to ships' kinematic from complementary data sources (environmental, contextual, geographical, …).

Passive stochastic matched filter for Antarctic blue whale call detection.

As a first step to Antarctic blue whale (ABW) monitoring using passive acoustics, a method based on the stochastic matched filter (SMF) is proposed. Derived from the matched filter (MF), this filter-based denoising method enhances stochastic signals embedded in an additive colored noise by maximizing its output signal to noise ratio (SNR). These assumptions are well adapted to the passive detection of ABW calls where emitted signals are modified by the unknown impulse response of the propagation channel.