Self-localization of a mobile swarm using noise correlations with local sources of opportunity.

Groups of coordinated underwater vehicles or sensors are powerful tools for monitoring the ocean. A requirement of many coordinated surveys is to determine a spatial reference between each node in a swarm. This work considers the self-localization of a swarm of independently moving vehicles using acoustic noise from a dominating incoherent source recorded by a single hydrophone onboard each vehicle. This method provides an inexpensive and infrastructure-free spatial reference between vehicles. Movement between the vehicles changes the swarm geometry and a self-localization estimate must be generated from data collected on short time scales. This challenges past self-localization approaches for acoustic arrays. To overcome this challenge, the proposed self-localization algorithm jointly estimates the vehicle geometry and the directionality of the ambient noise field, without prior knowledge of either estimate. To demonstrate this method, experimental results are provided when a boat is the main dominating source. The results demonstrate the ability to both estimate the direction of arrival of the boat and the relative positions of the vehicles in the swarm. The approach in this paper is not limited to moving vessels. Simulations are provided to examine three different factors that affect the proposed solution: inter-vehicle motion, vehicle geometry, and the azimuthal variance of the noise field.

A swarm of autonomous miniature underwater robot drifters for exploring submesoscale ocean dynamics.

Measuring the ever-changing 3-dimensional (3D) motions of the ocean requires simultaneous sampling at multiple locations. In particular, sampling the complex, nonlinear dynamics associated with submesoscales (<1-10 km) requires new technologies and approaches. Here we introduce the Mini-Autonomous Underwater Explorer (M-AUE), deployed as a swarm of 16 independent vehicles whose 3D trajectories are measured near-continuously, underwater. As the vehicles drift with the ambient flow or execute preprogrammed vertical behaviours, the simultaneous measurements at multiple, known locations resolve the details of the flow within the swarm. We describe the design, construction, control and underwater navigation of the M-AUE. A field programme in the coastal ocean using a swarm of these robots programmed with a depth-holding behaviour provides a unique test of a physical-biological interaction leading to plankton patch formation in internal waves. The performance of the M-AUE vehicles illustrates their novel capability for measuring submesoscale dynamics.

Ambient noise correlations on a mobile, deformable array.

This paper presents a demonstration of ambient acoustic noise processing on a set of free floating oceanic receivers whose relative positions vary with time. It is shown that it is possible to retrieve information that is relevant to the travel time between the receivers. With thousands of short time cross-correlations (10 s) of varying distance, it is shown that on average, the decrease in amplitude of the noise correlation function with increased separation follows a power law. This suggests that there may be amplitude information that is embedded in the noise correlation function. An incoherent beamformer is developed, which shows that it is possible to determine a source direction using an array with moving elements and large element separation. This incoherent beamformer is used to verify cases when the distribution of noise sources in the ocean allows one to recover travel time information between pairs of mobile receivers.