Ship Location Research Articles

The performance of Tiangong-2 InIRA in gravity anomaly recovery from fused conventional nadir-observing altimeter data

Satellite altimetry has emerged as the primary data source for deriving marine gravity, owing to advancements in satellite altimetry technologies. The Tiangong-2 interferometric imaging radar altimeter (TG2 InIRA) is a new generation wide-swath altimeter (WSA) launched by China on 15 September 2016. TG2 InIRA employs a short-baseline interferometry measurement method at a small incidence angle, thereby enabling the precise measurement of wide-swath sea surface heights (SSHs). The present study demonstrates the efficacy of utilizing data from the TG2 InIRA in conjunction with data from the CryoSat-2 (CS2) satellite to recover marine gravity anomalies. In the Northwest Pacific region (15°N ∼ 25°N, 140°E ∼ 150°E), the TG2 InIRA data were filtered to a 2 km × 2 km grid and any anomalous values were excluded using a mean sea surface model. Deflections of the vertical (DOVs) were calculated using the remove-restore technique, and the inverse Vening-Meinesz formula was applied to invert the gravity anomaly. A power spectral density analysis was conducted to assess variations in gravity anomalies at ship locations in the frequency domain. The results, based on the SIO V31.1 (DOV) model, indicate that the gridded vertical deflections derived from CS2 and TG2 InIRA data achieve more balanced accuracy in the east–west and north–south directions. The integration of TG2 InIRA and CS2 data yielded gravity results exhibiting a root mean square (RMS) of 0.519 mGal lower than those derived from TG2 InIRA data alone, and 0.034 mGal lower than those derived from CS2 data. These findings were derived from shipborne gravity data. Furthermore, the inversion of gravity anomalies from TG2 InIRA demonstrated an enhanced capability in the reduction of high-frequency gravity noise.

A major midlatitude hurricane in the Little Ice Age

Abstract. An unusually severe hurricane (Louisbourg Storm) struck Nova Scotia, Canada, in 1757. Historic records describing storm conditions as well as damage to ships and coastal fortifications indicate an intensity beyond any modern (post-1851) Atlantic cyclones striking the same region, yet this storm struck during a cold climate period known as the Little Ice Age (LIA). Its track and timing coincided with a British naval blockade of a French fleet at Fortress Louisbourg during the Seven Years' War (1756–1763). This provides a unique opportunity to explore growing scientific evidence of heightened storminess in the North Atlantic despite a colder climate expected to suppress hurricane intensification but which research is increasingly showing to have supported North Atlantic storms of exceptional strength. Weather attributes extracted from the logs of naval vessels scattered by the Louisbourg Storm provided multiple hourly observations recorded at different locations. Wave height and wind force estimates at ship locations were compared to extreme storm surge heights calculated for Louisbourg Harbour and a shipwreck site south of Fortress Louisbourg. Comparing these metrics to those of modern analogues that crossed the same bathymetry reflects landfall intensity consistent with a powerful major hurricane. Historical records show this storm originated as a tropical cyclone at the height of hurricane season and intensified into the northern midlatitudes along the Gulf Stream. Its intensity at landfall is consistent with established seasonal climatological models where highly baroclinic westerlies driven by autumn continental cooling encounter intensifying north-tracking tropical cyclones fuelled by sea surface temperatures that peak in autumn. Stronger seasonal contrasts from earlier and colder continental westerlies in the Little Ice Age (LIA) may have triggered explosive extratropical transition from a large hurricane resulting in a more severe strike. It suggests that tropical cyclones lasting days to weeks and the conditions that generate them are likely masked by cooler historic mean annual to multi-decadal LIA climate reconstructions.

Interactions Between Lightning and Ship Traffic

AbstractIt is important to understand connections between society and the natural environment for anticipating hazards and anthropogenic effects on the Earth system. In this study, we conduct a detailed exploration of interactions between oceanic thunderstorms and maritime traffic. Shipping traffic produces aerosols that perturb the otherwise “clean” ocean environment. Prior work proposed these aerosol effects as the cause of increased lightning over certain shipping lanes. However, introducing tall grounded objects into a high electric field environment might also facilitate lightning discharges, as we see with upward lightning over land. We consider both possibilities. Our analyses of the thunderstorms responsible for enhanced lightning activity over the shipping lane with the clearest anthropogenic signal indicate that the enhancement results from an increased frequency of lightning‐producing storms. Observed variations in thunderstorm microphysics between the shipping lane and nearby oceans are small compared to natural factors such as the Indian monsoon, and are on the same scale as the local variability in the data. By contrast, matching lightning stroke data with ship transponder events in oceanic regions where public data are available reveals a strong signal from direct ship interactions. Lightning is 15× (66×) more likely to occur at a ship location compared to 2 km (25 km) away. These results highlight the central role of direct ship interactions in explaining lightning enhancements over shipping lanes. We also document the frequency of these direct lightning interactions across various categories of vessels and on individual ships present in the public data.

Method for monitoring and improving the accuracy characteristics of shipboard satellite navigation equipment

The aim of the study is to improve approaches to monitoring and control of electronic systems of water transport, as well as navigation support itself, to improve navigation safety by developing a method for monitoring and improving the accuracy characteristics of shipboard satellite navigation equipment in real operating conditions. The article considers the importance of modern ship radio navigation systems for ensuring safety of navigation and highlights the limitations that may arise during operation of these systems. In this regard, the authors of the article propose an approach to monitoring and improving the accuracy of satellite navigation equipment of a ship in real conditions of ship operation. The article considers the use of a ground-based control and measurement station to control the precise characteristics of shipboard satellite navigation equipment. This station is installed on shore and operates based on the basic equation of metrology. The positioning system of a laser locator ship is described as follows: The GPS navigation spacecraft sends a laser beam to an optical angle reflector mounted on the vessel, and then a ground-based control and measurement station measures the time it takes for the laser beam to travel to and from the reflector, which allows the distance to the vessel to be calculated. The data is then transmitted to user equipment on the ship, which uses it in conjunction with the spacecraft's GPS navigation data to determine the ship's location, time and speed. The features of this approach are its high accuracy and applicability in various conditions, including poor visibility. To consider the geometric differences between the antennas of the ground control and measuring station and the user's equipment, as well as to consider the roll and pitch, the authors propose to use geometric ratios. The use of the method of accuracy control of shipboard satellite navigation equipment based on a ground-based control and measuring station proposed in the article allows to determine errors with high accuracy in various conditions of real operation, which contributes to the improvement of navigation safety

Accuracy of GNSS Position Stored in Fishing Boat Location Transmitters in Comparison with That of DGPS Position

Fishing boat laws in Korea require fishing boats to be equipped with a location transmitter. Approximately 91% of registered fishing boats have V-pass terminals, whereas those with a gross tonnage of 10 t or more have either V-pass or automatic identification system (AIS) terminals (or use both). Most navigators, including the fishing boat location transmitter, rely on the satellite signals provided by the global navigation satellite system (GNSS) without considering the accuracy of the navigation instruments that indicate ship location. Many scholars are conducting research to analyze the accuracy of GNSS locations through continuous experiments; however, few of them focus on fishing boat location transmitters. Particularly, the location accuracy of V-pass equipment is unknown. Notably, the V-pass and AIS terminals used in fishing boats are mainly designed to locate fishing boats in need of assistance following a marine accident rather than to provide information on approaching ships and preventing collisions. Therefore, this study aimed to compare GNSS location storage data extracted from the location transmitter (V-pass and AIS terminal) of the accident fishing boat with the DGPS location information from the Electronic Chart Display and Information System to check the position error and use it for accident analysis and investigation.

Ship detection and classification based on cascaded detection of hull and wake from optical satellite remote sensing imagery

ABSTRACT Satellite remote-sensing provides a cost- and time-effective tool for ship monitoring at sea. Most existing approaches focused on extraction of ship locations using either hull or wake. In this paper, a method of cascaded detection of ship hull and wake was proposed to locate and classify ships using high-resolution satellite imagery. Candidate hulls were fast located through phase spectrum of Fourier transform. A hull refining module was then executed to acquire accurate shapes of candidate hull. False alarms were removed through the shape features and textures of candidate hulls. The probability that a candidate hull is determined as a real one increased with the presence of wakes. After true ships were determined, ship classification was conducted using a fuzzy classifier combining both hull and wake information. The proposed method was implemented to Gaofen-1 panchromatic and multispectral (PMS) imagery and showed good performance for ship detection with recall, precision, overall accuracy, and specificity of 90.1%, 88.1%, 98.8%, and 99.3%, respectively, better than other state-of-the-art coarse-to-fine ship detection methods. Ship classification was successfully achieved for ships with detected wakes. The accuracy of correct classification was 83.8% while the proportion of false classification was 1.0%. Factors influencing the accuracy of the developed method, including texture features and classifiers combination and key parameters of the method, were also discussed.

AARN: Anchor‐guided attention refinement network for inshore ship detection

AbstractInshore ship detection is an important task in several fields, for example, maritime transportation, maritime supervision, and port management. However, due to the diversified categories and locations of different ships and interference of complex surroundings, capturing discriminative characteristics of multi‐scale inshore ships for accurate detection is still challenging. Here, an anchor‐guided attention refinement network (AARN) is proposed to alleviate the problems by prominently designing an attention feature filter module (AFFM) and an anchor‐guided alignment detection module (AADM). In AFFM, of which the attention supervision generated from high‐level semantic features, is used to highlight informative target cues and suppress background interference when establishing a four‐layer feature pyramid. In AADM, the anchor‐aligned features are adopted to eventually identify potential inshore ships, which both alleviates misalignment between refined anchors and pyramidal features and improves the performance further. Extensive experiments conducted on the public Seaships7000 dataset verify the contributions of the proposed modules and the effectiveness of our method for detecting multi‐scale inshore ships in comparison to both domain‐specific and general CNN‐based methods.

Marine ship instance segmentation by deep neural networks using a global and local attention (GALA) mechanism.

Marine ships are the transport vehicle in the ocean and instance segmentation of marine ships is an accurate and efficient analysis approach to achieve a quantitative understanding of marine ships, for example, their relative locations to other ships or obstacles. This relative spatial information is crucial for developing unmanned ships to avoid crashing. Visible light imaging, e.g. using our smartphones, is an efficient way to obtain images of marine ships, however, so far there is a lack of suitable open-source visible light datasets of marine ships, which could potentially slow down the development of unmanned ships. To address the problem of insufficient datasets, here we built two instance segmentation visible light datasets of marine ships, MariBoats and MariBoatsSubclass, which could facilitate the current research on instance segmentation of marine ships. Moreover, we applied several existing instance segmentation algorithms based on neural networks to analyze our datasets, but their performances were not satisfactory. To improve the segmentation performance of the existing models on our datasets, we proposed a global and local attention mechanism for neural network models to retain both the global location and semantic information of marine ships, resulting in an average segmentation improvement by 4.3% in terms of mean average precision. Therefore, the presented new datasets and the new attention mechanism will greatly advance the marine ship relevant research and applications.

Improved Multitarget Tracking in the Presence of Port–Starboard Measurement Ambiguity Using the Bayes Factor

We consider an application where an unmanned underwater vehicle (UUV) equipped with an acoustic sensor seeks to estimate the location of surface ships using relative angle measurements to the ships. The estimation problem is challenging due to ships occasionally appearing and disappearing from the sensor's field of view. On occasion, poor geometry between the sensor and the ships, and port–starboard ambiguity that is inherent in the sensor contribute to the challenges in the estimation problem. The latter challenge arises because the sensor cannot distinguish between sound sources on its port and starboard side (port–starboard ambiguity). Therefore, every measurement is associated with two possible sound sources that map each relative angle to bearing projections on the port and starboard side of the UUV. We approach the problem of identifying the origin of sound sources (relative angle measurements) that are most likely to be of actual ships using Bayesian hypothesis testing. We propose an assignment method that uses the Bayes factor as the criteria to recursively associate measurements to the target that is most likely to be an actual ship and not a false target. The effectiveness of our approach is evaluated by comparing the performance of three multitarget tracking algorithms with and without our method. Performance is evaluated offline using sea-trial data captured by a UUV developed by the Naval Research Laboratory and Bluefin Robotics.

Semantic Recognition of Ship Motion Patterns Entering and Leaving Port Based on Topic Model

Recognition and understanding of ship motion patterns have excellent application value for ship navigation and maritime supervision, i.e., route planning and maritime risk assessment. This paper proposes a semantic recognition method for ship motion patterns entering and leavingport based on a probabilistic topic model. The method enables the discovery of ship motion patterns from a large amount of trajectory data in an unsupervised manner and makes the results more interpretable. The method includes three modules: trajectory preprocessing, semantic process, and knowledge discovery. Firstly, based on the activity types and characteristics of ships in the harbor waters, we propose a multi-criteria ship motion state recognition and voyage division algorithm (McSMSRVD), and ship trajectory is divided into three sub-trajectories: hoteling, maneuvering, and normal-speed sailing. Secondly, considering the influence of port traffic rules on ship motion, the semantic transformation and enrichment of port traffic rules and ship location, course, and speed are combined to construct the trajectory text document. Ship motion patterns hidden in the trajectory document set are recognized using the Latent Dirichlet allocation (LDA) topic model. Meanwhile, topic coherence and topic correlation metrics are introduced to optimize the number of topics. Thirdly, a visualization platform based on ArcGIS and Electronic Navigational Charts (ENCs) is designed to analyze the knowledge of ship motion patterns. Finally, the Tianjin port in northern China is used as the experimental object, and the results show that the method is able to identify 17 representative inbound and outbound motion patterns from AIS data and discover the ship motion details in each pattern.

Short-Term Trajectory Prediction of Maritime Vessel Using k-Nearest Neighbor Points

The prediction of ship location has become an increasingly popular research hotspot in the field of maritime transportation engineering, which benefits maritime safety supervision and security. Existing methods of ship location prediction based on motion characteristics have a large uncertainty and cannot guarantee trajectory prediction accuracy of the target ship. An improved method of location prediction using k-nearest neighbor (KNN) is proposed in this paper. An expanded circle area of the latest point of the target ship is first generated to find the reference points with similar movement characteristics in the constraints of distance and time intervals. Then, the top k-nearest neighbors are determined based on the degree of similarity. Relationships between the reference point of each neighbor and the latest points of the target ship are calculated. The predicted location of the target ship can then be determined by a weighted calculation of the locations of all neighbors at the predicted time and their relationships with the target ship. Experiments of ship location prediction in 10 min, 20 min, and 30 min were conducted. The correlation coefficient of the location prediction error for the three experiments was 0.992, 0.99, and 0.9875, respectively. The results show that ship location prediction with reference to multiple nearest neighbors with similar movements can provide better accuracy.

Naval doctors in the Russian-Japanese War (1904–1905)

The article presents integrated data on the sea-going forces and the location of ships of the 1st Pacifi c Squadron during the Russian-Japanese War of 1904–1905. Particular attention is paid to the distribution of doctors of the Siberian and Kwantung naval crews among the ships of the fl eet. The most complete data on the participation of navy doctors in battles and in the defense of Port Arthur are presented. Their fate after the wreck of the squadron is traced.

Evaluation of ship operational effect based on long-term encountered sea states using wave hindcast combined with storm avoidance model

Ships avoid severe sea states for the safety of lives and property and to save energy. Therefore, the actual sea states encountered by ships differ from nature and are affected by human operational effects that we refer to as the “ship operational effect”. The evaluation of the ship operational effect is crucial for the rational design of structural strength of the hull. In this study, we derived the sea states encountered over 25 years in the North Atlantic, by considering storm avoidance by merchant ships. We then performed long-term predictions of the ship motions and wave loads of 75 merchant ships. Existing pioneering studies used automatic identification system (AIS)-based ship locations and timestamps to subsample wave hindcast data along ship tracks for a limited duration. Unlike existing studies, we used a statistical storm avoidance model of merchant ships to reconstruct the sea states, encountered over 25 years, in the North Atlantic. Owing to the ship operational effect, the long-term prediction values of roll motion, pitch motion, vertical bending moment amidships, and hydrodynamic pressure on bottom centerline amidships of merchant ships, at the probability level 10−8, were reduced by approximately 10–20%, and the coefficient of the ship operational effect was 0.8–0.9. Furthermore, we evaluated the uncertainties in the ship operational effect. The values deviated by as much as 6%, depending on the choice of wave hindcast products (TodaiWW3-NK, IOWAGA, and ERA5). The variation based on the parameter settings of the storm avoidance model (severity of the storm, radius of influence of the storm, and number of ship locations) was up to approximately 1 m at a probability level of 10−5 of the encountered sea states for 25 years.

The impact of oil prices on world trade

AbstractIn this article, we investigate the importance of fuel costs in shaping trade. We use AIS data on ship locations and transaction‐level shipping prices, along with a dynamic model describing the shipping industry, to measure the elasticity of bulk goods trade with respect to ship fuel costs. We find that the average estimated elasticity is 0.35, but ranges from 0.1 to about 1.2 depending on the level of the fuel cost. The pass‐through of fuel costs to transport costs is low, at 0.17. Strikingly, this elasticity features a pronounced asymmetry in low versus high oil prices. As fuel costs decline, the elasticity plateaus and further declines have little impact on trade. This “flattening out” of the elasticity is attributed to the equilibrium of the transportation sector and in particular the changes in the relative bargaining positions of ships and exporters. Finally, we use the estimated elasticity to assess the importance of ship design on trade flows: if the large fuel efficiency gains achieved in the 1980s had not been realized, trade would be 12% lower today.

SIMULATION TECHNIQUES IN THE DEVELOPMENT OF THE QUIESCENT PERIOD PREDICTION (QPP) FLIGHT DECK MOTION FORECASTING TOOL

Quiescent Period Prediction (QPP) purpose is to provide ship motion conditions and motion predictions with sufficient forecasted time to launch, recover, and complete other motion sensitive tasks regardless of the seaway. QPP operates within a federated architecture system containing measurement instruments such as a Wave Radar system used to map remote sea surfaces several hundred meters in advance of the ship. This enables the computation of future wave forces acting on the virtual vessel. Quiescent Period Prediction (QPP) system achieves this from the measured sea surface, a short-term deterministic wave model can be constructed allowing the wave system to be propagated to the ship's location. The ability to fully define a ship’s motion as a function of a recovery device, greatly enhances the overall system operational capability whilst fundamentally reducing the inherent risks associated with platform manipulation in high sea conditions. This article describes launch and recovery simulation model and the corresponding verification and validation of the QPP data program testing the accuracy of the simulation modeling. Verification information is discussed regarding the sensor operation and interfaces collected during this trial; a QPP simulation design specification is being produced based on High Level Architecture (HLA) technics. From initial simulation and trial results, QPP has been shown to offer the ability for operators to identify the most favourable deck motion periods to recover an approaching vehicle. The next challenge being studied from the data results is a notional navigational guidance system tool and visual landing aid to be trialled by simulation.

Development of the Hub and Spoke network model in natural disaster management

Indonesia is a country with high disaster vulnerability. Disasters have a huge impact on a nation’s economic development. According to the National Agency for Disaster Management, a disaster is an event or a series of events that threatens and disrupts the lives and livelihoods of people, caused by either natural factors and/or non-natural factors, as well as human factors and resulting in human casualties to lead. Environmental damage, property damage and psychological impact. This study is limited to hazards caused by natural factors, including nine types of threats, namely: earthquakes, tsunamis, volcanic eruptions, landslides, floods, flash floods, drought, forest and land fires, and extreme waves and abrasion. As an archipelago country, Indonesia has challenges in disaster management. Another thing behind this study is that there is a discrepancy between disaster maps and the location (distribution) of ships that have the potential to be deployed in disaster management, which will affect the duration of the emergency response time and the high cost of disaster management. What’s more, there are conditions in which ships cannot perform certain coping functions, affecting the inability to effectively treat disaster victims, potentially increasing fatalities. Not all ships are suitable for disaster response operations in specific areas, resulting in the emergency response time being too long and the cost of disaster response being high. The purpose of this study is to evaluate the effectiveness of the existing ship distribution state that can be used in disaster management versus the existing disaster map. The research method used is to collect data and identify potential disasters in Indonesia. Then collect data and map the type and number of ships and the distribution of ship bases that can be used in disaster management. Using qualitative analysis, assess the discrepancy between vessel availability and distribution and the potential location and nature of the disaster in Indonesia. The expected result is that there is a match between the availability and distribution of vessels and the potential of the location and nature of the disaster in Indonesia.

Teleconsultation at Sea and Acute Wound Management Onboard.

Introduction: The French Tele-Medical Assistance Service (TMAS) provides medical teleconsultation for any ship at sea. At the end of the consultation, the doctor decides whether the problem can be taken care of onboard or not. In this study, we determined the factors associated with the decision for disembarkation or evacuation in case of wounds. Methods: We conducted a retrospective epidemiological study between 2011 and 2019 from consultations with the French TMAS. The inclusion criterion was the presence of an acute wound. Results: One thousand six patients (n = 1,006) were analyzed and 586 (58%) patients were disembarked or evacuated. Factors associated with disembarkation or evacuation are wound characteristics (severity and location), the onboard staff's medical training, the availability of photography, and the ship's location. Wound severity is a risk factor for disembarkation or evacuation. The availability of photography, staff with advanced training, and being at >1 day of navigation from a harbor are protective factors against being disembarked or evacuated. Conclusion: The added value of photography and an update of medium medical training could increase the number of wounds taken care of onboard.

Use of pulsars for ship navigation: an alternative to the sextant

AbstractA new method is proposed for determining a ship's position at sea using naturally occurring pulsar signals to provide an alternative to the sextant. Use is made of four distinct pulsar radio signals whose timing stabilities are comparable to atomic clocks and whose characteristic signatures can be used as natural radio navigation beacons. Pulse peak time difference measurements, accurate to within 10−5and 10−6s, were generated for a key reference observatory which provides long-term pulsar timing observations and for the unknown ship location. These time differences when multiplied by the velocity of light provide a distance value that is fundamental in calculating the ship's position. Resultant simulations provided a position accuracy to ≈1⋅1 km (≈0⋅6 nm) for the higher timing difference measurement. A single-pulsar-based approach, which gave a position accuracy to ≈2⋅8 km (≈1⋅5 nm), was also investigated for affordable equipment solutions and comparison with NASA space-based navigation experiments.

Research on strategic liner ship fleet planning with regard to hub-and-spoke network

In order to obtain the biggest economic benefits, large shipping firms widely use hub-and-spoke network to operate ships. The reasonable shipping network not only decreases the cost of infrastructure construction to achieve scale economies, but also be efficient to allocate the existing resources of maritime business. Shipping firms usually are in pursuit of the large-scale container ship, leading some firms to blindly upgrade vessels and cause the loss of profit. Since the operating costs and transportation time is the major problem for shipping firms to get more profit, in this study, we research the relationship of route design, fleet planning and container freight to build the objective function in view of the minimization of time and cost. This study proposes the mixed integer linear programming model of hub-and-spoke network and liner ship fleet planning to choose the appropriate ship location and distribution, and applies Lagrange Heuristic Algorithm to solve the model. The simulation results verify the validity of this algorithm, showing that when firms invest the large ship, it usually gets lower freight rate, by contrast, small vessels have cost and scale advantages. But in order to cope with changes in market demand, for the operations of shipping firms, owning large vessels are still necessary. Our two-phase model considers problems comprehensively to complete the network design of liner ship fleet planning. Lagrange Heuristic Algorithm can get high quality solutions in a relatively short time, it provides reference significance for solving related problems in the future.

해양사고 대비 해상교통안전 정보제공기관의 법적 및 제도적 고찰

This study enacted the Ship Traffic Control Act in 2019 to reduce the risk of marine accidents and improve the safety and efficiency of ship traffic, and the Korea Coast Guard operates ports and coastal VTS. Ship traffic control provides safety information and port operation information to ships by installing and operating equipment capable of detecting the location of ships and communicating with ships, and is essential for the safety of ship traffic. However, institutions that provide safety information to ships are distributed to various institutions as well as the Korea Coast Guard, and operate inefficiently, analyzing the operation of maritime traffic safety information in preparation for marine accidents.