Oceanographic Data Collection Research Articles

An underwater acoustic communication scheme exploiting biological sounds

AbstractUnderwater acoustic (UWA) communications have attracted a lot of interest in recent years motivated by a wide range of applications including offshore oil field exploration and monitoring, oceanographic data collection, environmental monitoring, disaster prevention, and port security. Different signaling solutions have been developed to date including non‐coherent communications, phase coherent systems, multi‐input and multi‐output solutions, time‐reversal‐based communication systems, and multi‐carrier transmission approaches. This paper deviates from the traditional approaches to UWA communications and develops a scheme that exploits biomimetic signals. In the proposed scheme, a transmitter maps the information bits to the parameters of a biomimetic signal, which is transmitted over the channel. The receiver estimates the parameters of the received signal and demaps them back to bits to estimate the message. As exemplary biomimetic signals, analytical signal models with nonlinear instantaneous frequency are developed that match mammal sound signatures in the time‐frequency plane are developed. Suitable receiver structures as well as performance analysis are provided for the proposed transmission scheme, and some results using data recorded during the Kauai Acomms MURI 2011 UWA communications experiment are presented. Copyright © 2016 John Wiley & Sons, Ltd.

Guest Editorial Special Issue on Advances in Underwater Acoustic Sensor Networks

With the advances in vehicle and sensor technologies, there is a growing interest in the design and deployment of Underwater Acoustic Sensor Networks (UASNs). A typical UASN employs underwater nodes, surface sinks, autonomous underwater vehicles and low-power gliders to collaboratively perform underwater operating missions. For the ease of deployment as well as the ability in intellectualization information processing, UASNs are envisioned to enable marine applications for oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance. Compared with traditional monitoring technologies, e.g., remote sensing or sonar sweeping, USANs have clear advantages in terms of infrastructureless, real-time, high-precision and low-cost detection.

Dynamic Collaboration Between Networked Robots and Clouds in Resource-Constrained Environments

Underwater mobile sensor networks such as Autonomous Underwater Vehicles (AUVs) or robots are envisioned to enable applications for oceanographic data collection, environmental and pollution monitoring, offshore exploration, and distributed tactical surveillance. These applications require running compute- and data-intensive algorithms that go beyond the capabilities of the individual AUVs that are involved in a mission. To execute these task-parallel algorithms in resource- and time-constrained environments, dynamic and reliable collaboration between local networked robots (e.g., AUVs) and remote public Clouds is needed. To this end, the heterogeneous sensing, computing, communication, and storage capabilities of local and remote resources are exploited to form a “loosely coupled” mobile Cloud, and a novel resource provisioning engine that dynamically takes decisions on “what” and “where” the tasks should be executed in the mobile Cloud is introduced. Comparison of benefits of collaboration between local and Cloud resources with purely local and centralized approaches are presented through exhaustive computer simulations.

Bio-logging of marine migratory species in the law of the sea

The use of advanced and emerging remote data-collection technologies, and in particular bio-logging of marine migratory species, raises fundamental questions about the scope of authority of coastal states to regulate marine scientific research in the waters under their jurisdiction. Bio-logging involves the attachment of devices to marine animals that collect and transmit data about their movements and aspects of the local marine environment, and is now routinely used by marine scientists to support conservation programs and augment oceanographic data collection. Tagged marine life, including seabirds, marine mammals, sea turtles and pelagic fishes, may interact unpredictably with the territorial seas and exclusive economic zones (EEZs) of numerous coastal states. This article explores the legal implications of bio-logging within the legal regime of marine scientific research in the law of the sea. Although bio-logging is a form of marine scientific research, when it is initiated outside a coastal state׳s jurisdiction it does not later fall within it, even if the tagged animals subsequently enters a coastal state׳s territorial sea or EEZ.

The common oceanographer: crowdsourcing the collection of oceanographic data.

We live on a vast, underexplored planet that is largely ocean. Despite modern technology, Global Positioning System (GPS) navigation, and advanced engineering of ocean vessels, the ocean is unforgiving, especially in rough weather. Coastal ocean navigation, with risks of running aground and inconsistent weather and sea patterns, can also be challenging and hazardous. In 2012, more than 100 international incidents of ships sinking, foundering, grounding, or being lost at sea were reported (http://en.wikipedia.org/wiki/List_of_shipwrecks_in_2012). Even a modern jetliner can disappear in the ocean with little or no trace [1], and the current costs and uncertainty associated with search and rescue make the prospects of finding an object in the middle of the ocean daunting [2]. Notwithstanding satellite constellations, autonomous vehicles, and more than 300 research vessels worldwide (www.wikipedia.org/wiki/List_of_research_vessels_by_country), we lack fundamental data relating to our oceans. These missing data hamper our ability to make basic predictions about ocean weather, narrow the trajectories of floating objects, or estimate the impact of ocean acidification and other physical, biological, and chemical characteristics of the world's oceans. To cope with this problem, scientists make probabilistic inferences by synthesizing models with incomplete data. Probabilistic modeling works well for certain questions of interest to the scientific community, but it is difficult to extract unambiguous policy recommendations from this approach. The models can answer important questions about trends and tendencies among large numbers of events but often cannot offer much insight into specific events. For example, probabilistic models can tell us with some precision the extent to which storm activity will be intensified by global climate change but cannot yet attribute the severity of a particular storm to climate change. Probabilistic modeling can provide important insights into the global traffic patterns of floating debris but is not of much help to search-and-rescue personnel struggling to learn the likely trajectory of a particular piece of debris left by a wreck. Oceanographic data are incomplete because it is financially and logistically impractical to sample everywhere. Scientists typically sample over time, floating with the currents and observing their temporal evolution (the Langrangian approach), or they sample across space to cover a gradient of conditions—such as temperature or nutrients (the Eulerian approach). These observational paradigms have various strengths and weaknesses, but their fundamental weakness is cost. A modern ocean research vessel typically costs more than US$30,000 per day to operate—excluding the full cost of scientists, engineers, and the cost of the research itself. Even an aggressive expansion of oceanographic research budgets would not do much to improve the precision of our probabilistic models, let alone to quickly and more accurately locate missing objects in the huge, moving, three-dimensional seascape. Emerging autonomous technologies such as underwater gliders and in situ biological samplers (e.g., environmental sample processors) help fill gaps but are cost prohibitive to scale up. Similarly, drifters (e.g., the highly successful Argo floats program) have proven very useful for better defining currents, but unless retrieved after their operational lifetime, they become floating trash, adding to a growing problem. Long-term sampling efforts such as the continuous plankton recorder in the North Sea and North Atlantic [3] provide valuable data on decadal trends and leveraged English Channel ferries to accomplish much of the sampling. Modernizing and expanding this approach is a goal of citizen science initiatives. How do we leverage cost-effective technologies and economies of scale given shrinking federal research budgets?

Current State of Technology of Fuel Cell Power Systems for Autonomous Underwater Vehicles

Autonomous Underwater Vehicles (AUVs) are vehicles that are primarily used to accomplish oceanographic research data collection and auxiliary offshore tasks. At the present time, they are usually powered by lithium-ion secondary batteries, which have insufficient specific energies. In order for this technology to achieve a mature state, increased endurance is required. Fuel cell power systems have been identified as an effective means to achieve this endurance but no implementation in a commercial device has yet been realized. This paper summarizes the current state of development of the technology in this field of research. First, the most adequate type of fuel cell for this application is discussed. The prototypes and design concepts of AUVs powered by fuel cells which have been developed in the last few years are described. Possible commercial and experimental fuel cell stack options are analyzed, examining solutions adopted in the analogous aerial vehicle applications, as well as the underwater ones, to see if integration in an AUV is feasible. Current solutions in oxygen and hydrogen storage systems are overviewed and energy density is objectively compared between battery power systems and fuel cell power systems for AUVs. A couple of system configuration solutions are described including the necessary lithium-ion battery hybrid system. Finally, some closing remarks on the future of this technology are given.

Exploiting Adaptive and Collaborative AUV Autonomy for Detection and Characterization of Internal Waves

Advances in the fields of autonomy software and environmental sampling techniques for autonomous underwater vehicles (AUVs) have recently allowed for the merging of oceanographic data collection with the testing of emerging marine technology. The Massachusetts Institute of Technology (MIT) Laboratory for Autonomous Marine Sensing Systems (LAMSS) group conducted an Internal Wave Detection Experiment in August 2010 with these advances in mind. The goal was to have multiple AUVs collaborate autonomously through onboard autonomy software and real-time underwater acoustic communication to monitor for the presence of internal waves by adapting to changes in the environment (specifically the temperature variations near the thermocline/pycnocline depth). The experimental setup, implementation, data, deployment results, and internal wave detection and quantification results are presented in this paper.

Linking Acoustic Communications and Network Performance: Integration and Experimentation of an Underwater Acoustic Network

Underwater acoustic networks (UANs) are an emerging technology for a number of oceanic applications, ranging from oceanographic data collection to surveillance applications. However, their reliable usage in the field is still an open research problem, due to the challenges posed by the oceanic environment. The UAN project, a European-Union-funded initiative, moved along these lines, and it was one of the first cases of successful deployment of a mobile underwater sensor network integrated within a wide-area network, which included above water and underwater sensors. This contribution, together with a description of the underwater network, aims at evaluating the communication performance, and correlating the variation of the acoustic channel to the behavior of the entire network stack. Results are given based on the data collected during the UAN11 (May 2011, Trondheim Fjord area, Norway) sea trial. During the experimental activities, the network was in operation for five continuous days and was composed of up to four Fixed NOdes (FNOs), two autonomous underwater vehicles (AUVs), and one mobile node mounted on the supporting research vessel. Results from the experimentation at sea are reported in terms of channel impulse response (CIR) and signal-to-interference-plus-noise ratio (SINR) as measured by the acoustic modems during the sea tests. The performance of the upper network levels is measured in terms of round trip time (RTT) and probability of packet loss (PL). The analysis shows how the communication performance was dominated by variations in signal-to-noise ratio, and how this impacted the behavior of the whole network. Qualitative explanation of communication performance variations can be accounted, at least in the UAN11 experiment, by standard computation of the CIR and transmission loss estimate.

Risk‐aware Path Planning for Autonomous Underwater Vehicles using Predictive Ocean Models

Recent advances in Autonomous Underwater Vehicle (AUV) technology have facilitated the collection of oceanographic data at a fraction of the cost of ship‐based sampling methods. Unlike oceanographic data collection in the deep ocean, operation of AUVs in coastal regions exposes them to the risk of collision with ships and land. Such concerns are particularly prominent for slow‐moving AUVs since ocean current magnitudes are often strong enough to alter the planned path significantly. Prior work using predictive ocean currents relies upon deterministic outcomes, which do not account for the uncertainty in the ocean current predictions themselves. To improve the safety and reliability of AUV operation in coastal regions, we introduce two stochastic planners: (a) a Minimum Expected Risk planner and (b) a risk‐aware Markov Decision Process, both of which have the ability to utilize ocean current predictions probabilistically. We report results from extensive simulation studies in realistic ocean current fields obtained from widely used regional ocean models. Our simulations show that the proposed planners have lower collision risk than state‐of‐the‐art methods. We present additional results from field experiments where ocean current predictions were used to plan the paths of two Slocum gliders. Field trials indicate the practical usefulness of our techniques over long‐term deployments, showing them to be ideal for AUV operations.

Thermohaline structure and water masses in the north of Antarctic Peninsula from data collected in situ by southern elephant seals (Mirounga leonina)

A Península Antártica Oeste é uma das regiões do planeta que está se aquecendo rapidamente e apresenta alta diversidade animal principalmente ao longo de sua plataforma continental. Esta região também é de grande importância devido à mistura causada pela interação de águas do Mar de Weddell (MW), do Estreito de Bransfield (EB) e da Corrente Circumpolar Antártica (CCA) que transmitem características termohalinas e nutrientes de diferentes locais de formação e mais tarde se conectam com todos os oceanos do planeta. Entretanto, estudos sobre a variabilidade temporal das condições oceanográficas desta região que consequentemente determinam a formação de massas d'água, são escassos em função das dificuldades logísticas envolvidas em levantamentos oceanográficos e monitoramentos tradicionais durante os meses de inverno. Para esse trabalho, variações da estrutura termohalina e das massas d'água nas proximidades e abaixo do gelo marinho na região norte da Península Antártica (PA) e Mar da Escócia (ME) foram registradas entre os meses de fevereiro e novembro de 2008 por duas fêmeas de elefante-marinho do sul (EMS, Mirounga leonina) instrumentadas com Conductivity - Temperature - Depth/Satellite-Relay Data Logger (CTD - SRDL). 1330 perfis verticais de temperatura e salinidade foram coletados por estes indivíduos que foram instrumentados pelo Projeto MEOP-BR na Ilha Elefante, Shetlands do Sul. Esses perfis, juntamente com diagramas de estado espalhado permitiram a identificação de massas d'água e suas alterações na estrutura vertical oceânica. Dentre as massas d'água identificadas citamos: Água de Superfície Antártica (AASW), Água de Inverno (WW), Água Cálida Profunda (WDW), Água Cálida Profunda Modificada (MWDW), Água Circumpolar Profunda (CDW), Água Profunda Circumpolar Superior (UCDW), Água Profunda Circumpolar Inferior (LCDW) e Água de Plataforma de Gelo (ISW). Nossos resultados mostram que a estrutura vertical oceânica sofre alterações que tradicionalmente não podem ser monitoradas, principalmente durante o inverno austral, e que os EMS são importantes e modernas plataformas para coleta de dados oceanográficos, permitindo um aumento em nosso conhecimento dos processos oceanográficos na região antártica.

Performance Evaluation of Underwater Sensor Networks

Recent improvements in wireless communications and acoustic technology have enabled the use of sensor networks in underwater Surface. Underwater Sensor Networks is an emerging field which requires research in the field of routing and channel access. Applications Using offshore exploration, assisted navigation, Oceanographic data collection and tactical surveillance applications use underwater sensor networks. Some applications such as disaster prevention require minimum delay in data gathering. And also care must be taken to make sure that the energy expenditure of an underwater sensor node is minimal because replenishment of a sensor node is not cost-effective. Simulation results have demonstrated that information-directed routing is a significant improvement over a previously reported 3DUT algorithm, as measured by sensing quality such as localization, tracking accuracy and using Ad hoc network communication quality such as success rate in routing around sensor holes.

The advantage of FM slide signals for active acoustic systems used for fisheries studies.

A key requirement for many active acoustics systems used for fisheries or biological oceanographic data collection is to provide high spatial resolution while maximizing the range for which useful data are obtained. Unfortunately, most systems in use today use cw pulse transmit signals for which the user must trade‐off range resolution with output signal‐to‐noise, which determines the maximum useful range at which data can be collected. This paper describes the application of a different type of signal, the FM slide or chirp, for fisheries and oceanographic acoustic assessment. Compared to the cw pulse based systems, acoustic systems that use FM slide signals with the corresponding matched filter processing can achieve significantly better spatial resolution without sacrificing maximum range. The explanation of why the FM slide signal achieves this improved performance as well as a discussion of some of the factors that must be considered when implementing this signal type are described. Laboratory measurements and field results are presented that show the advantages of the FM slide for real world assessment studies.

Asymmetrical Round Trip Based Synchronization-Free Localization in Large-Scale Underwater Sensor Networks

Underwater sensor networks (UWSNs) have been proposed for many location-dependent applications such as oceanographic data collection, pollution monitoring, mine reconnaissance, etc. Accurate node localization plays an important role in realizing the potential gains of these applications. Although many localization algorithms have been proposed for terrestrial sensor networks in recent years, it is not feasible to directly use these algorithms in UWSNs since UWSNs lack a fast and reliable communication channel. Further, due to their slow convergence speeds and high communication overhead, distributed localization algorithms designed for small-scale UWSNs are not practical for large-scale underwater sensor systems. To achieve accurate and energy efficient node localization in large-scale UWSNs, an asymmetrical round trip based localization (ARTL) algorithm is proposed in this paper. This algorithm has low computational complexity and excellent scalability. Without time synchronization, this algorithm can achieve highly accurate ranging in large-scale UWSNs. Simulation results demonstrate the effectiveness of our design in terms of both localization accuracy and energy consumption.

Fisheries replenishment of early life taxa: potential export of fish eggs and larvae from a temperate marine protected area

AbstractAn ichthyoplankton survey was conducted at the periphery of Cabrera National Park (Balearic Islands, Western Mediterranean Sea) in July 2004, using bongo nets, fixed nets and collection of oceanographic data. This work focused on analysing the distribution of eggs and larval stages of some fishery‐targeted taxa (Coris julis, Epinephelus spp., Sciaena umbra and Scorpaena sp.) whose adult abundances and/or biomass are higher in the reserve and therefore would be likely to show gradients of larval abundance attributable to the existence of the Marine Protected Area (MPA). Oceanographic data indicated there was water column stratification, horizontal distribution of surface water masses and hydrodynamic features linked with Mediterranean seasonality. During the summer sampling, eggs and larvae of targeted fish taxa were mainly located in the northeast of the MPA, near the coast. An effect of depth and current was demonstrated for Coris julis and Epinephelus spp. and there appears to be an offshore gradient for the other targeted taxa, especially for the egg stages. These data highlight the fact that the Cabrera archipelago is a potential important spawning area for targeted fishery species.

USC CINAPS Builds Bridges

More than 70% of our earth is covered by water, yet we have explored less than 5% of the aquatic environment. Aquatic robots, such as autonomous underwater vehicles (AUVs), and their supporting infrastructure play a major role in the collection of oceanographic data. To make new discoveries and improve our overall understanding of the ocean, scientists must make use of these platforms by implementing effective monitoring and sampling techniques to study ocean upwelling, tidal mixing, and other ocean processes. Effective observation and continual monitoring of a dynamic system as complex as the ocean cannot be done with one instrument in a fixed location. A more practical approach is to deploy a collection of static and mobile sensors, where the information gleaned from the acquired data is distributed across the network. Additionally, orchestrating a multisensor, long-term deployment with a high volume of distributed data involves a robust, rapid, and cost-effective communication network. Connecting all of these components, which form an aquatic robotic system, in synchronous operation can greatly assist the scientists in improving our overall understanding of the complex ocean environment.

Changing the tide of forecasts

This article presents a general discussion on the forecasting capabilities provided by the Integrated Ocean Observing System and its applications to oceanographic science and data collection.

Mapping bathymetric and hydrographic features of Glover's Reef, Belize, with a REMUS autonomous underwater vehicle

We used an autonomous underwater vehicle (AUV) to survey bathymetry and water mass properties at Glover's Reef atoll in Belize as part of a multidisciplinary study of population connectivity of Nassau grouper (Epinephelus striatus). Nassau grouper populations are declining dramatically throughout its range in the Caribbean because of overfishing. In response, Marine Protected Areas have been established at several spawning aggregation (SPAG) sites. However, effectiveness of these measures is presently unclear, as the regional patterns of transport and recruitment of grouper larvae have not been measured in extensive field studies. As part of a pilot study to relate oceanographic processes with transport and recruitment of Nassau grouper larvae, we used a Remote Environmental Monitoring Unit(S) (REMUS) AUV to measure the bathymetry, stratification, current velocity, and chlorophyll a fluorescence around Glover's Reef. The portability of the REMUS system enabled comprehensive oceanographic data collection in a remote location with minimal infrastructure. Using REMUS, we were able to effectively map the bathymetry of the reef and the shelfbreak. These data were merged with historical bathymetric data to develop a new chart of the atoll margin. A distinct contrast in the width of the shelves on the eastern and western sides of the atoll was demonstrated, with the widest shelf coinciding with the SPAG site. Water mass structure in the vicinity of SPAG site was also markedly different from other locations on the reef, suggesting an offshore advective influence on eggs and early‐stage larvae released there.

Three-dimensional and two-dimensional deployment analysis for underwater acoustic sensor networks

Underwater sensor networks find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation, and tactical surveillance. In this paper, deployment strategies for two-dimensional and three-dimensional communication architectures for underwater acoustic sensor networks are proposed, and a mathematical deployment analysis for both architectures is provided. The objective is to determine the minimum number of sensors to be deployed to achieve optimal sensing and communication coverage, which are dictated by application requirements; provide guidelines on how to choose the optimal deployment surface area, given a target body of water; study the robustness of the sensor network to node failures, and provide an estimate of the number of redundant sensor nodes to be deployed to compensate for potential failures.

Designing Underwater Cellular Networks Parameters

Oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance are some of the applications of underwater networks. Underwater networks should send the gathered information to other users or an offshore station via a base station in the sea. Since the available bandwidth in underwater is severely limited, frequency reuse and cellular networks concepts are very important. In this paper, after driving the ratio of signal to interference for underwater acoustic channels, the constraints for the cell radius are determined. One of the important results of this work is that, for special parameters like bandwidth, it may be impossible to provide the required signal to interference ratio and bandwidth for the network users. Furthermore, in this paper, number of supportable users, per-user bandwidth, and the user capacity for a cellular underwater network are determined.

An observing system for the collection of fishery and oceanographic data

Abstract. Fishery Observing System (FOS) was developed as a first and basic step towards fish stock abundance nowcasting/forecasting within the framework of the EU research program Mediterranean Forecasting System: Toward an Environmental Prediction (MFSTEP). The study of the relationship between abundance and environmental parameters also represents a crucial point towards forecasting. Eight fishing vessels were progressively equipped with FOS instrumentation to collect fishery and oceanographic data. The vessels belonged to different harbours of the Central and Northern Adriatic Sea. For this pilot application, anchovy (Engraulis encrasicolus, L.) was chosen as the target species. Geo-referenced catch data, associated with in-situ temperature and depth, were the FOS products but other parameters were associated with catch data as well. MFSTEP numerical circulation models provide many of these data. In particular, salinity was extracted from re-analysis data of numerical circulation models. Satellite-derived sea surface temperature (SST) and chlorophyll were also used as independent variables. Catch and effort data were used to estimate an abundance index (CPUE – Catch per Unit of Effort). Considering that catch records were gathered by different fishing vessels with different technical characteristics and operating on different fish densities, a standardized value of CPUE was calculated. A spatial and temporal average CPUE map was obtained together with a monthly mean time series in order to characterise the variability of anchovy abundance during the period of observation (October 2003–August 2005). In order to study the relationship between abundance and oceanographic parameters, Generalized Additive Models (GAM) were used. Preliminary results revealed a complex scenario: the southern sector of the domain is characterised by a stronger relationship than the central and northern sector where the interactions between the environment and the anchovy distribution are hidden by a higher percentage of variability within the system which is still unexplained. GAM analysis showed that increasing the number of explanatory variables also increased the portion of variance explained by the model. Data exchange and interdisciplinary efforts will therefore be crucial for the success of this research activity.