Paul L. D. Roberts

Designing an Adaptive Acoustic Modem for Underwater Sensor Networks

There is a growing interest in using underwater networked systems for oceanographic applications. These networks often rely on acoustic communication, which poses a number of challenges for reliable data transmission. The underwater acoustic channel is highly variable; each link can experience vastly different conditions, which change according to environmental factors as well as the locations of the communicating nodes. This makes it difficult to ensure reliable communication. Furthermore, due to the high transmit power, the energy consumed in transmitting data is substantial, which is exacerbated at lower data rates. The main challenge that we address in this article is how to build a system that provides reliable and energy efficient communication in underwater sensor networks. To this end, we propose an adaptive underwater acoustic modem which changes its parameters according to the situation. We present the design of such a modem and provide supporting results from simulations and experiments.

Classification of live, untethered zooplankton from observations of multiple-angle acoustic scatter

A broadband, multiple-angle acoustic array was used to classify millimeter to centimeter sized live zooplankton in a laboratory tank. Reflections in the frequency range from 1.5 to 2.5 MHz were recorded from untethered 1-4 mm calanoid copepods and 8-12 mm mysids over an angular range of 0 degrees -47 degrees . A synchronized, coregistered video system recorded animal location and orientation. To highlight differences between animals, a frequency correlation matrix was computed from the observed wide-band power spectra of the scattered sound. Significant differences in the slopes and shapes of the eigenvalue spectra of this matrix were found for mysids versus copepods. These results support the idea that broadband, multiple-angle scatter can be used to classify organisms of different sizes and shapes.

An Autonomous Open-Ocean Stereoscopic PIV Profiler

Abstract Over the past decade, a novel free-fall imaging profiler has been under development at the Scripps Institution of Oceanography to observe and quantify biological and physical structure in the upper 100 m of the ocean. The profiler provided the first detailed view of microscale phytoplankton distributions using in situ planar laser-induced fluorescence. The present study examines a recent incarnation of the profiler that features microscale turbulent flow measurement capabilities using stereoscopic particle image velocimetry (PIV). As the profiler descends through the water column, a vertical sheet of laser light illuminates natural particles below the profiler. Two sensitive charge-coupled device (CCD) cameras image a 25 cm × 25 cm × 0.6 cm region at a nominal frame rate of 8 Hz. The stereoscopic camera configuration allows all three components of velocity to be measured in the vertical plane with an average spatial resolution of approximately 3 mm. The performance of the PIV system is evaluated ...

Multiple angle acoustic classification of zooplankton.

The use of multiple angle acoustic scatter to discriminate between two taxa of fluid-like zooplankton, copepods and euphausiids, is explored. Using computer modeling, feature extraction, and subsequent classification, the accuracy in discriminating between the two taxa is characterized via computer simulations. The model applies the distorted wave Born approximation together with a simple system geometry, a linear array, to predict a set of noisy training and test data. Three feature spaces are designed, exploiting the relationship between the shape of the scatterer and angularly varying scattering amplitude, to extract discriminant features from these data. Under the assumption of uniform random length and uniform three-dimensional orientation distributions for each class of scatterers, the performance of several classification algorithms is evaluated. Simulations reveal that the incorporation of multiple angle data leads to a marked improvement in classification performance over single angle methods. The improvement is more substantial using broadband scatter. The simulations indicate that under the stated assumptions, a low classification error can be obtained. The use of multiple angle scatter therefore holds promise to substantially improve the in situ acoustic classification of fluid-like zooplankton using simple observation geometries.

Wide Field-of-View Fluorescence Imaging of Coral Reefs

Coral reefs globally are declining rapidly because of both local and global stressors. Improved monitoring tools are urgently needed to understand the changes that are occurring at appropriate temporal and spatial scales. Coral fluorescence imaging tools have the potential to improve both ecological and physiological assessments. Although fluorescence imaging is regularly used for laboratory studies of corals, it has not yet been used for large-scale in situ assessments. Current obstacles to effective underwater fluorescence surveying include limited field-of-view due to low camera sensitivity, the need for nighttime deployment because of ambient light contamination, and the need for custom multispectral narrow band imaging systems to separate the signal into meaningful fluorescence bands. Here we describe the Fluorescence Imaging System (FluorIS), based on a consumer camera modified for greatly increased sensitivity to chlorophyll-a fluorescence, and we show high spectral correlation between acquired images and in situ spectrometer measurements. This system greatly facilitates underwater wide field-of-view fluorophore surveying during both night and day, and potentially enables improvements in semi-automated segmentation of live corals in coral reef photographs and juvenile coral surveys.

Multiview, Broadband Acoustic Classification of Marine Fish: A Machine Learning Framework and Comparative Analysis

Multiview, broadband, acoustic classification of individual fish was investigated using a recently developed laboratory scattering system. Scattering data from nine different species of saltwater fish were collected. Using custom software, these data were processed and filtered to yield a data set of 36 individuals, and between 200 and 500 echoes per individual. These data were sampled uniformly randomly in fish orientation. Feature-, decision-, and collaborative-fusion algorithms were then developed and tested using support vector machines (SVMs) as the underlying classifiers. Decision fusion was implemented by cascading two levels of support vectors machines. Collaborative fusion was implemented by using SVM outputs to estimate confidence levels and performing weighted averaging of probabilities computed from each view with feedback from other views. Collaborative fusion performed as well or better than the others, and did so without requiring assumptions about view geometry. In addition to a comparison between classification algorithms and feature transformations, two data collection geometries were explored, including random observation geometries. In all cases, combining multiple, broadband views yielded significant reductions in classification error (>;50%) over single-view methods, for uniformly random fish orientation.

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.

Underwater microscopy for in situ studies of benthic ecosystems

Microscopic-scale processes significantly influence benthic marine ecosystems such as coral reefs and kelp forests. Due to the oceans complex and dynamic nature, it is most informative to study these processes in the natural environment yet it is inherently difficult. Here we present a system capable of non-invasively imaging seafloor environments and organisms in situ at nearly micrometre resolution. We overcome the challenges of underwater microscopy through the use of a long working distance microscopic objective, an electrically tunable lens and focused reflectance illumination. The diver-deployed instrument permits studies of both spatial and temporal processes such as the algal colonization and overgrowth of bleaching corals, as well as coral polyp behaviour and interspecific competition. By enabling in situ observations at previously unattainable scales, this instrument can provide important new insights into micro-scale processes in benthic ecosystems that shape observed patterns at much larger scales.

AUE: An Autonomous Float for Monitoring the Upper Water Column

A new autonomous underwater vehicle for exploring the upper water column has been developed. The Autonomous Underwater Explorer (AUE) is a 25 cm diameter sphere whose mission is to monitor currents in the upper 100 m of the ocean via either underwater acoustic tracking or by providing a (lat, Ion) fix via GPS after surfacing. Equipped with both temperature and depth sensors the float is capable of tracking both isotherms and isobars by adjusting its density via a piston that changes the volume of the vehicle. Equipped with an acoustic modem we envision fleets of such systems tracking water parcels in coastal regions while reporting their positions to each other and a surface ship in real time. Equipped with more advanced sensors such as fluorometers, nutrient sensors, or other miniature advanced devices, such small autonomous systems have the promise to provide a more synoptic view of the water column than heretofore possible.

Acoustic reflections on marine populations

Armed with a simple diffraction-based model, an acoustic oceanographer can bounce sound off marine animals to learn important information about their size and orientation.