Search Results (12)

Underwater optical imaging plays a crucial role in maritime safety, enabling reliable navigation, efficient search and rescue operations, precise target recognition, and robust military reconnaissance. However, conventional underwater imaging methods often suffer from severe backscattering noise, limited detection range, and reduced image clarity—challenges that are exacerbated in turbid waters. To address these issues, Underwater Laser Range-Gated Imaging has emerged as a promising solution. By selectively capturing photons within a controlled temporal gate, this technique effectively suppresses backscattering noise-enhancing image clarity, contrast, and detection range. Nevertheless, residual noise within the imaging slice can still degrade image quality, particularly in challenging underwater conditions. In this study, we propose an enhanced U-Net neural network designed to mitigate noise interference in underwater laser range-gated images, improving target recognition performance. Built upon the U-Net architecture with added residual connections, our network combines a VGG16-based perceptual loss with Mean Squared Error (MSE) as the loss function, effectively capturing high-level semantic features while preserving critical target details during reconstruction. Trained on a semi-synthetic grayscale dataset containing synthetically degraded images paired with their reference counterparts, the proposed approach demonstrates improved performance compared to several existing underwater image restoration methods in our experimental evaluations. Through comprehensive qualitative and quantitative evaluations, underwater target detection experiments, and real-world oceanic validations, our method demonstrates significant potential for advancing maritime safety and related applications. Full article

The paper addresses the dynamics modeling of underwater vehicles that are inertia propelled, i.e., they can move based upon the change of the amount of water in their water tanks and the motion of an internal mass, enabling maneuvers. Underwater vehicles of this type can be successfully applied in ocean scientific reconnaissance and exploration missions or for water pollution monitoring. Usually, dynamics modeling methods for them are based upon the Newton–Euler or Lagrange approaches modified to encompass variable mass. The main motivation of this research is to explore other modeling methods and compare them to those traditionally used. In this paper, modeling methods based on the Maggi and Boltzmann–Hamel approaches are presented and discussed with respect to their effectiveness in modeling, operation, and control applications. The resulting comparisons indicate that the traditional approaches are sufficient for the analysis of vehicle operation and performance in the realization of simple tasks; however, they become of limited application when the variable mass or constraints on vehicle dynamics or motion are added or complex maneuvers are required. In this regard, the Maggi or Boltzmann–Hamel approaches are more effective for dynamics modeling. The theoretical development is illustrated by examples of vehicle dynamics developed using the approaches we propose. Full article

As an emerging direction of multi-agent collaborative control technology, multiple autonomous underwater vehicle (multi-AUV) cooperative area search technology has played an important role in civilian fields such as marine resource exploration and development, marine rescue, and marine scientific expeditions, as well as in military fields such as mine countermeasures and military underwater reconnaissance. At present, as we continue to explore the ocean, the environment in which AUVs perform search tasks is mostly unknown, with many uncertainties such as obstacles, which places high demands on the autonomous decision-making capabilities of AUVs. Moreover, considering the limited detection capability of a single AUV in underwater environments, while the area searched by the AUV is constantly expanding, a single AUV cannot obtain global state information in real time and can only make behavioral decisions based on local observation information, which adversely affects the coordination between AUVs and the search efficiency of multi-AUV systems. Therefore, in order to face increasingly challenging search tasks, we adopt multi-agent reinforcement learning (MARL) to study the problem of multi-AUV cooperative area search from the perspective of improving autonomous decision-making capabilities and collaboration between AUVs. First, we modeled the search task as a decentralized partial observation Markov decision process (Dec-POMDP) and established a search information map. Each AUV updates the information map based on sonar detection information and information fusion between AUVs, and makes real-time decisions based on this to better address the problem of insufficient observation information caused by the weak perception ability of AUVs in underwater environments. Secondly, we established a multi-AUV cooperative area search system (MACASS), which employs a search strategy based on multi-agent reinforcement learning. The system combines various AUVs into a unified entity using a distributed control approach. During the execution of search tasks, each AUV can make action decisions based on sonar detection information and information exchange among AUVs in the system, utilizing the MARL-based search strategy. As a result, AUVs possess enhanced autonomy in decision-making, enabling them to better handle challenges such as limited detection capabilities and insufficient observational information. Full article

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV) that can be easily adapted for different types of land and/or water missions with low monetary cost (EUR < 5 k, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then, a market research analysis focused on vehicles currently available and their technological advances is conducted to identify existing UV solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle with approximate dimensions of 1050 × 670 × 450 mm (length–width–height), enabled with 6 × 6 traction capable of reaching 20 km/h on land, which possesses amphibious capabilities of independent propulsion in water up to 8 kts and an estimated autonomy of over 60 min. Full article

To meet the requirements of amphibious exploration, ocean exploration, and military reconnaissance tasks, a pneumatic amphibious soft bionic robot was developed by taking advantage of the structural characteristics, motion forms, and propulsion mechanisms of the sea lion fore-flippers, inchworms, Carangidae tails, and dolphin tails. Using silicone rubber as the main material of the robot, combined with the driving mechanism of the pneumatic soft bionic actuator, and based on the theory of mechanism design, a systematic structural design of the pneumatic amphibious soft bionic robot was carried out from the aspects of flippers, tail, head–neck, and trunk. Then, a numerical simulation algorithm was used to analyze the main executing mechanisms and their coordinated motion performance of the soft bionic robot and to verify the rationality and feasibility of the robot structure design and motion forms. With the use of rapid prototyping technology to complete the construction of the robot prototype body, based on the motion amplitude, frequency, and phase of the bionic prototype, the main execution mechanisms of the robot were controlled through a pneumatic system to carry out experimental testing. The results show that the performance of the robot is consistent with the original design and numerical simulation predictions, and it can achieve certain maneuverability, flexibility, and environmental adaptability. The significance of this work is the development of a pneumatic soft bionic robot suitable for amphibious environments, which provides a new idea for the bionic design and application of pneumatic soft robots. Full article

Oceanic intraplate volcanoes sometimes experience late-stage eruptive activity known as rejuvenated volcanism, and contrasting interpretations for its petrogenesis depend on the compositional characteristics. In the Juan Fernández Ridge (JFR), a volcanic chain approximately 800 km in length emplaced on the Nazca Plate, some subaerial occurrences of rejuvenated volcanism have been recognized on the Robinson Crusoe and Santa Clara Islands, both part of the same deeply eroded shield volcano complex. This study aims to understand the origin and magmatic evolution of rejuvenated volcanism on Santa Clara Island, emplaced after ~2.15 Ma of quiescence above the shield sequence, mainly via the analysis of unpublished geochemical and isotopic data. Field reconnaissance identified two nearly coeval rejuvenated sequences on Santa Clara Island: Bahía W (BW) and Morro Spartan (MS), both formed by basanitic and picro-basaltic lava flows with brecciated levels and local intercalations of sedimentary and pyroclastic deposits. In comparison to the chemical signature of the preceding shield-building stage (comprised mainly of basalts and picrites), the two rejuvenated sequences exhibit a notable enrichment in incompatible elements, but the Sr, Nd, and Pb isotopes are very similar to the FOZO mantle endmember, with an apparent additional contribution of HIMU and EM1 components. The geochemistry of lavas revealed the involvement of various processes, including contamination by ultramafic xenoliths, high-pressure fractional crystallization of olivine and clinopyroxene, and potential partial assimilation of oceanic lithospheric components. While the oceanic lithosphere has been considered as a potential source, the isotopic data from Santa Clara lies outside of the mixing curve between depleted mantle (DM, here represented by the North Chile Rise and the East Pacific Rise) and the previous shield stage, suggesting that a lithospheric mantle is not the primary source for the rejuvenated stage volcanism. Therefore, we favor an origin of the rejuvenated volcanism from the mantle plume forming the JFR, supported by similarities in isotopic signatures with the shield stage and high values of ²⁰⁸Pb/²⁰⁴Pb (only comparable to San Félix—San Ambrosio in the vicinity of JFR), implying the presence of a regional source with radiogenic ²⁰⁸Pb/²⁰⁴Pb isotope ratios. In addition, isotopic variations are subparallel to the mixing line between HIMU and EM1 components, whose participation in different proportions might explain the observed trends. In conclusion, we propose that the source of the rejuvenated volcanism on Santa Clara Island is a heterogeneous mantle plume, the same one that fed the shield stage. The rejuvenated volcanism is derived from a secondary melting zone away from the main axis of the plume. Full article

Increasing the density of Global Navigation Satellite System radio occultation (RO) with commercial Smallsats and the next generation COSMIC-2 constellation is expected to improve analyses of the state of atmosphere, which is essential for numerical weather prediction. High vertical resolution RO profiles could be useful to observe atmospheric rivers (ARs) over the ocean, which transport water vapor in shallow, elongated corridors that frequently impact the west coasts of continents. The multi-year AR Reconnaissance campaign has extensively sampled ARs over the northeastern Pacific with dropsondes, providing an invaluable dataset to evaluate the reliability of RO retrievals. These dropsondes, and a reanalysis product that assimilates them, are compared to three RO datasets: (1) established operational missions, (2) COSMIC-2, and (3) the commercial Spire constellation. Each RO dataset has biases relative to reanalyses of less than 0.5% N in the upper troposphere and negative biases in the lower troposphere. Direct colocations with dropsondes indicate that vertical refractivity gradients present within ARs may be contributing to negative biases at higher altitudes inside than outside ARs, where the greatest variability and vertical gradients are at the well-defined boundary layer top. Observations from Spire are overly smooth, affecting the ability to resolve the low-level structure of an AR. Surprisingly, the depth of penetration into the lower troposphere is greater inside an AR than outside for all datasets. The results indicate that the observation errors used for assimilation of RO within ARs should consider the height dependent biases that are associated with the structure of the atmosphere. Full article

Salinity is the primary determinant of the Arctic Ocean’s density structure. Freshwater accumulation and distribution in the Arctic Ocean have varied significantly in recent decades and certainly in the Beaufort Gyre (BG). In this study, we analyze salinity variations in the BG region between 2012 and 2017. We use in situ salinity observations from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), CTD casts from the Beaufort Gyre Exploration Project (BGP), and the EN4 data to validate and compare with satellite observations from Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Aquarius Optimally Interpolated Sea Surface Salinity (OISSS), and Arctic Ocean models: ECCO, MIZMAS, HYCOM, ORAS5, and GLORYS12. Overall, satellite observations are restricted to ice-free regions in the BG area, and models tend to overestimate sea surface salinity (SSS). Freshwater Content (FWC), an important component of the BG, is computed for EN4 and most models. ORAS5 provides the strongest positive SSS correlation coefficient (0.612) and lowest bias to in situ observations compared to the other products. ORAS5 subsurface salinity and FWC compare well with the EN4 data. Discrepancies between models and SIZRS data are highest in GLORYS12 and ECCO. These comparisons identify dissimilarities between salinity products and extend challenges to observations applicable to other areas of the Arctic Ocean. Full article

As a new type of marine unmanned intelligent equipment, autonomous underwater vehicle (AUV) has been widely used in the field of ocean observation, maritime rescue, mine countermeasures, intelligence reconnaissance, etc. Especially in the underwater search mission, the technical advantages of AUV are particularly obvious. However, limited operational capability and sophisticated mission environments are also difficulties faced by AUV. To make better use of AUV in the search mission, we establish the DMACSS (distributed multi-AUVs collaborative search system) and propose the ACSLA (autonomous collaborative search learning algorithm) integrated into the DMACSS. Compared with the previous system, DMACSS adopts a distributed control structure to improve the system robustness and combines an information fusion mechanism and a time stamp mechanism, making each AUV in the system able to exchange and fuse information during the mission. ACSLA is an adaptive learning algorithm trained by the RL (Reinforcement learning) method with a tailored design of state information, reward function, and training framework, which can give the system optimal search path in real-time according to the environment. We test DMACSS and ACSLA in the simulation test. The test results demonstrate that the DMACSS runs stably, the search accuracy and efficiency of ACSLA outperform other search methods, thus better realizing the cooperation between AUVs, making the DMACSS find the target more accurately and faster. Full article

With the operational deployment of the Stepped Frequency Microwave Radiometer (SFMR), hurricane reconnaissance and research aircraft provide near real-time observations of the 10 $\mathrm{m}$ ocean-surface wind-speed both within and around tropical cyclones. Hurricane specialists use these data to assist in determining wind radii and maximum sustained winds—critical parameters for determining and issuing watches and warnings. These observations are also used for post-storm analysis, model validation, and ground truth for aircraft- and satellite-based wind sensors. We present observations on the current operational wind-speed and rain-rate SFMR retrieval procedures in the tropical cyclone environment and propose suggestions to improve them based on observed wind-speed biases. Using these new models in the SFMR retrieval process, we correct an approximate 10% low bias in the wind-speed retrievals from 15 to 45 $\mathrm{m}$ $\mathrm{s}$ ⁻¹ with respect to GPS dropwindsondes. In doing so, we eliminate the rain-contaminated wind-speed retrievals below 45 mm $\mathrm{h}$ ⁻¹ at tropical storm- and hurricane-force speeds present in the current operational model. We also update the SFMR radiative transfer model to include recent updates to smooth-ocean emissivity and atmospheric opacity models. All corrections were designed such that no changes to the current SFMR calibration procedures are required. Full article

Differences in synthetic aperture radar (SAR)-retrieved hurricane wind speeds from co-polarization and cross-polarization measurements are found to be correlated with rain rate. A quality index is proposed for the SAR-retrieved wind speed product to recognize heavy rain- affected areas by taking account of the different imaging mechanisms of the radar backscattering from the ocean surface via cross-polarization and co-polarization observations. A procedure is proposed to rectify wind retrievals in the rain-contaminated areas within the hurricane core, based on the theoretical physical profile for hurricanes. The effectiveness of the proposed methodology for heavy rain area recognition and wind speed reconstruction in the rain-affected areas is validated against step frequency microwave radiometer measurements from hurricane reconnaissance missions and the hurricane surface wind analysis product (HWIND). The quality flags provide confidence levels of hurricane surface winds from SAR, which together with the proposed method to correct wind retrievals in rain-contaminated areas, can contribute to improved operational applications of SAR-derived winds under hurricane conditions. Full article

This study examines the legal framework for ocean current energy policy and regulation to develop a metric for assessing the biological and geological characteristics of a seabed area with respect to the siting of OCE devices, a framework of criteria by which to assess seabed suitability (seabed suitability framework) that can facilitate the siting, and implementation of ocean current energy (OCE) projects. Seafloor geology and benthic biological data were analyzed in conjunction with seafloor core sample geostatistical interpolation to locate suitable substrates for OCE anchoring. Existing submarine cable pathways were considered to determine pathways for power transmission cables that circumvent biologically sensitive areas. Suitability analysis indicates that areas east of the Miami Terrace and north of recently identified deep-sea coral mounds are the most appropriate for OCE siting due to abundance of sand/sediment substrate, existing underwater cable route access, and minimal biological presence (i.e., little to no benthic communities). Further reconnaissance requires higher resolution maps of geological substrate and benthic community locations to identify specific OCE development locations, classify benthic conditions, and minimize potentially negative OCE environmental impacts. Full article