Ship Location Research Articles

Two-Axis Solar Tracker Applied With All-Electric Ship

The all-electric ship (AES) offers new hope for the reduction of fuel consumption and carbon emissions. To fully exploit the photovoltaics (PVs) installed on the AES, the two-axis solar tracker is proposed to find the best tilt and surface azimuth angles of PV panels. The tilt angle is computed by particle swarm optimization (PSO) regarding the time and ship location. The surface azimuth angle is adjusted according to the hemisphere. The dynamic performance of the proposed solar tracker is evaluated using MATLAB/Simulink simulation. According to the simulation results, the proposed solar tracker can obtain maximum energy all day, while the voyage time, fuel consumption, and carbon emissions are significantly reduced. Moreover, the proposed solar tracker can effectively operate under communication delay caused by the global positioning system (GPS).

THE DESIGN AND HYDRODYNAMIC ASSESSMENT OF A SUBMARINE CONCEPT WITH OFF-AXIS RESOLVING THE IMPACT OF SHIP’S DESIGN ON DECK AND WELL-DECK LAUNCH AND RECOVERY OPERATIONS BY APPLYING OF QUIESCENT PERIOD PREDICTION (QPP)

One of the most challenging tasks in the deployment of ship-based manned and unmanned VTOL aviation is the launch and recovery and deck handling operational performance on smaller ship platforms. The same may be said of ship Well-deck-based surface boats, like Rhib and LCACs. Awareness and prediction of the ship’s position and movement in the ocean is key to ship-based air operations by targeting the right time to deploy and recover. The ships above waterline design coupled by the propulsion systems, affects ship’s motion and ship motion induced air wake behaviour. MoD/University of Exeter’s Quiescent Period Prediction (QPP) Program Aims to deliver technologies which support launch and recovery from Naval assets, particularly in higher sea states. The Quiescent Period Prediction (QPP) system achieves this by using a wave sensor system to measure the sea surface several hundred meters in advance of the ship. 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 ship's response to the wave spectrum is calculated to determine the level of quiescence at the time of encounter. The results are mapped dynamically on speed-polar visual graphics providing the ship’s best course to steer to ensure encountering the quiescent zone in a timely manner. 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. The use of simulation, routinely considered in the UK, as an alternative to traditional approaches such as scale model testing and fullscale sea trials, to predict the safety and performance envelopes of platforms and systems, is discussed. Operating over deck whilst the ship is experiencing a quiescent period normally has the secondary effect of reduced air wake confusion. This is owing to fewer ship structure excursions into and out of the air flow. To better define off deck airflow around the ship a future QPP improvement will be the development and installation of a Doppler LiDAR federate. The objective of this work is to define ship-helicopter operational deck limits (SHOL), and then to safely expand ship operating deck limits. This article discusses the background to aircraft/ship operations in relation to QPP and goes on to consider both short term implementations (the Landing Period Designator System) and longer horizon deterministically predictive forms of QPP. This article describes the development of the QPP System concentrating on test procedures, timely seaway mapping and ship motion characteristics to complete specific motion sensitive task. An overview of the theory and application is provided concerning dynamic interface analysis with the focus on encountered forces and vehicle to platform response stability.

GCBANet: A Global Context Boundary-Aware Network for SAR Ship Instance Segmentation

Synthetic aperture radar (SAR) is an advanced microwave sensor, which has been widely used in ocean surveillance, and its operation is not affected by light and weather. SAR ship instance segmentation can provide not only the box-level ship location but also the pixel-level ship contour, which plays an important role in ocean surveillance. However, most existing methods are provided with limited box positioning ability, hence hindering further accuracy improvement of instance segmentation. To solve the problem, we propose a global context boundary-aware network (GCBANet) for better SAR ship instance segmentation. Specifically, we propose two novel blocks to guarantee GCBANet’s excellent performance, i.e., a global context information modeling block (GCIM-Block) which is used to capture spatial global long-range dependences of ship contextual surroundings, enabling larger receptive fields, and a boundary-aware box prediction block (BABP-Block) which is used to estimate ship boundaries, achieving better cross-scale box prediction. We conduct ablation studies to confirm each block’s effectiveness. Ultimately, on two public SSDD and HRSID datasets, GCBANet outperforms the other nine competitive models. On SSDD, it achieves 2.8% higher box average precision (AP) and 3.5% higher mask AP than the existing best model; on HRSID, they are 2.7% and 1.9%, respectively.

Improved monitoring of shipping NO<sub>2</sub> with TROPOMI: decreasing NO<sub><i>x</i></sub> emissions in European seas during the COVID-19 pandemic

Abstract. TROPOMI (TROPOspheric Monitoring Instrument) measurements of tropospheric NO2 columns provide powerful information on emissions of air pollution by ships on open sea. This information is potentially useful for authorities to help determine the (non-)compliance of ships with increasingly stringent NOx emission regulations. We find that the information quality is improved further by recent upgrades in the TROPOMI cloud retrieval and an optimal data selection. We show that the superior spatial resolution of TROPOMI allows for the detection of several lanes of NO2 pollution ranging from the Aegean Sea near Greece to the Skagerrak in Scandinavia, which have not been detected with other satellite instruments before. Additionally, we demonstrate that under conditions of sun glint TROPOMI's vertical sensitivity to NO2 in the marine boundary layer increases by up to 60 %. The benefits of sun glint are most prominent under clear-sky situations when sea surface winds are low but slightly above zero (±2 m s−1). Beyond spatial resolution and sun glint, we examine for the first time the impact of the recently improved cloud algorithm on the TROPOMI NO2 retrieval quality, both over sea and over land. We find that the new FRESCO+ (Fast Retrieval Scheme for Clouds from the Oxygen A band) wide algorithm leads to 50 hPa lower cloud pressures, correcting a known high bias, and produces 1–4×1015 molec. cm−2 higher retrieved NO2 columns, thereby at least partially correcting for the previously reported low bias in the TROPOMI NO2 product. By training an artificial neural network on the four available periods with standard and FRESCO+ wide test retrievals, we develop a historic, consistent TROPOMI NO2 data set spanning the years 2019 and 2020. This improved data set shows stronger (35 %–75 %) and sharper (10 %–35 %) shipping NO2 signals compared to co-sampled measurements from OMI. We apply our improved data set to investigate the impact of the COVID-19 pandemic on ship NO2 pollution over European seas and find indications that NOx emissions from ships reduced by 10 %–20 % during the beginning of the COVID-19 pandemic in 2020. The reductions in ship NO2 pollution start in March–April 2020, in line with changes in shipping activity inferred from automatic identification system (AIS) data on ship location, speed, and engine.

Probabilistic Maritime Trajectory Prediction in Complex Scenarios Using Deep Learning.

Maritime activity is expected to increase, and therefore also the need for maritime surveillance and safety. Most ships are obligated to identify themselves with a transponder system like the Automatic Identification System (AIS) and ships that do not, intentionally or unintentionally, are referred to as dark ships and must be observed by other means. Knowing the future location of ships can not only help with ship/ship collision avoidance, but also with determining the identity of these dark ships found in, e.g., satellite images. However, predicting the future location of ships is inherently probabilistic and the variety of possible routes is almost limitless. We therefore introduce a Bidirectional Long-Short-Term-Memory Mixture Density Network (BLSTM-MDN) deep learning model capable of characterising the underlying distribution of ship trajectories. It is consequently possible to predict a probabilistic future location as opposed to a deterministic location. AIS data from 3631 different cargo ships are acquired from a region west of Norway spanning 320,000 sqkm. Our implemented BLSTM-MDN model characterizes the conditional probability of the target, conditioned on an input trajectory using an 11-dimensional Gaussian distribution and by inferring a single target from the distribution, we can predict several probable trajectories from the same input trajectory with a test Negative Log Likelihood loss of corresponding to a mean distance error of km 50 min into the future. We compare our model to both a standard BLSTM and a state-of-the-art multi-headed self-attention BLSTM model and the BLSTM-MDN performs similarly to the two deterministic deep learning models on straight trajectories, but produced better results in complex scenarios.

Coastal Shipping Radar Monitoring System with Satellites as Transmitters of Opportunity

Introduction. With the development of technology and science, passive radar systems operating on the basis of third-party transmitters of illumination signal sources are increasingly attracting research interest. The use of satellite systems as transmitters of opportunity for a radar station makes it possible to monitor coastal sea areas, where the ground sources of illumination signals are absent. Satellite systems can cover any point on the Earth's surface. Passive radar systems can be used to determine the location of ships and monitor navigation. They are also promising as part of vessel traffic control systems.Aim. To develop a model of a passive radar system that uses satellite systems as third-party sources of illumination signals and to conduct an experimental study of a system for monitoring ships in coastal waters.Materials and methods. The AA2-KKС antennas of satellite signals and radio recording tools based on the universal USRP B210 board were used. Signal processing was performed using a program developed in the MATLAB environment.Results. An algorithm for processing satellite signals of the GPS global navigation system in a passive radar system is proposed. An experimental model of the receiving station for such a radar monitoring system was created on the basis of a data input device for a universal USRP board of the B210 series. Experimental results for the receiving station using the satellite signal GPS L1 C/A-code for coastal monitoring were obtained.Conclusion. The developed experimental model of a passive radar receiving station using third-party transmitters of GPS satellitebased illumination signals on the L1 frequency range of the C/A-code type can be used for detecting ships and monitoring coastal navigation. Future research will consider a multiposition modification of such a monitoring system for improving its detection quality and increasing its target positioning accuracy.

Mechanisms associated with the rapid decline in sea ice cover around a stranded ship in the Lazarev Sea, Antarctica

In the satellite data era starting from 1979, the extent of Antarctic sea ice increased moderately for the first 37 years. However, the extent decreased to record low levels from 2016 to 2020, with the drop being greatest in the Weddell and Lazarev Seas of the Southern Ocean. An important question for the scientific fraternity and policymakers is to understand what ocean-atmospheric processes triggered such a rapid decline in sea ice. We employ in-situ, satellite, and atmospheric reanalysis data to examine the causative mechanism of anomalous sea ice variability in the Lazarev Sea at a time of ice growth in the annual cycle (March–April 2019), when a cargo ship was stuck in extensive ice cover and freed following the unusual decline in sea ice. High-resolution Sentinel-1 synthetic aperture radar captured a distinct view of the ship location and track within extensive ice cover of fast sea ice, dense pack ice, and icebergs in the Lazarev Sea on 27 March 2019. Subsequently, the sea ice cover declined and reached the fourth lowest extent in the entire satellite record during April 2019 which was 25.6% lower than the long-term mean value of 2.65 × 106 km2. We show that the anomalous sea ice variability was due to the occurrence of eastward-moving polar cyclones, including a quasi-stationary explosive development that impacted sea ice through extreme changes in ocean-atmospheric conditions. The cyclone-induced dynamic (poleward propagation of ocean waves and ice motion) and thermodynamic (heat and moisture plumes from midlatitudes, ocean mixed layer warming) processes coupled with high tides provided a conducive environment for an exceptional decline in sea ice over the region of ship movement.

Importance and applicability analysis of the health and safety measures taken against the coronavirus disease on merchant vessels

The coronavirus (COVID-19) outbreak has affected seafarers worldwide. This paper demonstrates the measures taken to prevent the spread of the corona-virus on merchant ships and evaluates them in terms of importance and applicability. Contamination reducing measures were determined through expert opinion and literature review. While their importance values were calculated using the fuzzy analytic hierarchy process method in which the total integral value with optimism index was applied, the applicability levels were revealed using a fivepoint Likert scale. The imbalance in rest and working hours was clearly seen in the re-sults. Immune system pro-tective measures were the most critical measures; however, two of them have the lowest applicability val-ue among all criteria. They were followed by the measures taken through training, the measures to be applied in case of personnel showing disease symptoms, and the temperature measurement. In terms of the ship locations and ship operations, maintaining physical distance on deck at the port was found more critical. Its applicability level was slightly below average. This paper is the first study in the literature in which the measures taken to prevent the spread of the coronavirus pandemic on merchant ships were demonstrated in detail and evaluated with scientific methods in terms of importance and applicability. The research findings will help companies in the risk assessment process and contribute to the enhancement of the preparedness of the maritime industry for such situations by helping to protect the seafarers’ health and safety.

낚시어선의 안전에 관한 소고 - 해양안전심판원의 재결을 중심으로 -

The charter fishing boat business was legalized in 1995 to revitalize fishing trip and to increase income of fishing village. However, contrary to its original purpose, the number of fishing boats engaged only in the “charter fishing boat business” has increased, and is now transforming into a kind of leisure industry. According to the statistics from the Korea Maritime Safety Tribunal, a total of 1,215 accidents occurred in charter fishing boats over the five years from 2016 to 2020, during which the number of deaths and missing people in charter fishing boats’ accident was 24, and 120 were injured. Currently, marine accidents occurring in charter fishing boats are appearing in various aspects such as collision, stranded, capsizing, sinking, fire, and engine damage. In the case of a capsizing accident of charter fishing boat in 2015, the fishing boat departed the port despite the heavy weather, and the boat was capsized after leaving the port, saving only 3 of the 21 fishing passengers, and 18 including the captain, were dead or missing. In 2019, a charter fishing boat collided with another ship and was capsized, causing all 14 people to fall into the water and were exposed to cold seawater in the winter, killing five people. And it wss found that some captains intentionally turned off the “Ship Location Transmitters Equipmen”(V-Pass) to hide violations of business areas, causing difficulties in searching and rescue in case of distress. Charter fishing boats, along with passenger ships, excursion ship and ferry boats, are public-use ship and need institutional devices for the safety of fishing passengers. In this study, the accidents related to charter fishing boats over the past five years includeded in the “Annual Judgement Casebook” published by the Korean Maritime Safety Tribunal were analyzed to research measures to prevent or reduce accidents. And it was concluded that improvement of “annual professional education for charter fishing boat’s proprietors and crew” is necessary. In addition, it was also found that it is necessary to improve the institutional system or to revise some related laws and regulations for the safety of charter fishing boats.

Global Shipping Emissions from a Well-to-Wake Perspective: The MariTEAM Model.

Improving the robustness of maritime emission inventories is important to ensure we fully understand the point of embarkment for transformation pathways of the sector toward the 1.5 and 2°C targets. A bottom-up assessment of emissions of greenhouse gases and aerosols from the maritime sector is presented, accounting for the emissions from fuel production and processing, resulting in a complete “well-to-wake” geospatial inventory. This high-resolution inventory is developed through the use of the state-of-the-art data-driven MariTEAM model, which combines ship technical specifications, ship location data, and historical weather data. The CO2 emissions for 2017 amount to 943 million tonnes, which is 11% lower than the fourth International Maritime Organization’s greenhouse gas study for the same year, while larger discrepancies have been found across ship segments. If fuel production is accounted for when developing shipping inventories, total CO2 emissions reported could increase by 11%. In addition to fuel production, effects of weather and heavy traffic regions were found to significantly impact emissions at global and regional levels. The global annual efficiency for different fuels and ship segments in approximated operational conditions were also investigated, indicating the need for more holistic metrics than current ones when seeking appropriate solutions aiming at reducing emissions.

Indication of a ship location by the Earth’s geomagnetic field

The present study focuses on the need to increase the number of methods for indicating a ship location in traffic conditions on routes with heavy shipping, as well as during navigation in hard hydrometeorological conditions. The research purpose is to increase the level of safety and accuracy of ship navigation and effectively meet the requirements in the field of navigation safety and environmental protection. The issue of navigating through physical fields has a wide range of unresolved tasks despite the previously conducted studies. These tasks include investigation of geomagnetic sensors and their relationship to geomagnetic maps, as well as magnetic compasses and ways to improve them by using magnetometers and eliminating errors caused by rotation of the magnetic needle.

Ship detection from passive underwater acoustic recordings using machine learning

The Ocean Observatories Initiative (OOI) hydrophone data contains a rich collection of ship passage events that can be leveraged for passive ship detection. This study uses 6 years of OOI acoustic data collected by the hydrophone located at the southern foot of the Axial Seamount volcano with a sampling rate of 200 Hz. Ship location data from the Automatic Identification System (AIS) is used to predict the presence or absence of ships within an effective radius of the hydrophone, estimated to be 15 km. After, identifying ships with similar acoustic profiles, such as commercial carrier, tanker, cargo, container, and supply ships, a balanced dataset is created with an even distribution of ships within and outside of the estimated radius. The final dataset is separated into a training (70%), validation (10%), and test (20%) dataset, and then used to create k-nearest neighbors (KNN) and logistic regression models using the scikit-learn Python library. The KNN model achieves the best performance and classifies the ships with an accuracy of 98.04%. This shows that it is possible to determine the presence of ships from passive underwater acoustic recordings with high accuracy. [Work supported by the SURIEA program and ONR.]

GNSS-based water vapor estimation and validation during the MOSAiC expedition

Abstract. Within the transpolar drifting expedition MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate), the Global Navigation Satellite System (GNSS) was used among other techniques to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked GNSS data including GPS, GLONASS and Galileo, epoch-wise coordinates and hourly zenith total delays (ZTDs) were determined using a kinematic precise point positioning (PPP) approach. The derived ZTD values agree to 1.1 ± 0.2 mm (root mean square (rms) of the differences 10.2 mm) with the numerical weather data of ECMWF's latest reanalysis, ERA5, computed for the derived ship's locations. This level of agreement is also confirmed by comparing the on-board estimates with ZTDs derived for terrestrial GNSS stations in Bremerhaven and Ny-Ålesund and for the radio telescopes observing very long baseline interferometry in Ny-Ålesund. Preliminary estimates of integrated water vapor derived from frequently launched radiosondes are used to assess the GNSS-derived integrated water vapor estimates. The overall difference of 0.08 ± 0.04 kg m−2 (rms of the differences 1.47 kg m−2) demonstrates a good agreement between GNSS and radiosonde data. Finally, the water vapor variations associated with two warm-air intrusion events in April 2020 are assessed.

Determinants of medical evacuations from merchant cargo ships: Evidence from Telemedical Assistance Service of Turkey data

Seafarers are exposed to a greater risk of illness, injury, or death than onshore workers. They are also, deprived of the professional medical care and assistance provided for workers inshore. Medical evacuations are crucial for saving the lives of onboard seafarers. We, therefore, investigated the relationship between seafarer demographics, ship features, incident characteristics, and medical evacuation. The study included a total of 4668 contacts related to seafarers from merchant cargo ships to the Telemedical Assistance Service (TMAS) of Turkey, of which 471 incidents required a medical evacuation at sea. The Classification and Regression Tree (CART) approach and logistic regression were employed to analyse the medical evacuation cases. The most significant explanatory variable determining medical evacuation cases was ship location (Wald = 285.45, p = 0.00) while ship flag, ship age, ship type, seafarer age, working site of seafarer, and seafarer nationality were also statistically significant factors (p < 0.05). This study thus provides information on the factors affecting evacuations at sea. Understanding the risk factors leading to evacuations will ensure that appropriate measures are taken to prevent serious incidents and, timely evacuation decisions are made to save lives on board.

A path planning strategy unified with a COLREGS collision avoidance function based on deep reinforcement learning and artificial potential field

Improving the autopilot capability of ships is particularly important to ensure the safety of maritime navigation.The unmanned surface vessel (USV) with autopilot capability is a development trend of the ship of the future. The objective of this paper is to investigate the path planning problem of USVs in uncertain environments, and a path planning strategy unified with a collision avoidance function based on deep reinforcement learning (DRL) is proposed. A Deep Q-learning network (DQN) is used to continuously interact with the visually simulated environment to obtain experience data, so that the agent learns the best action strategies in the visual simulated environment. To solve the collision avoidance problems that may occur during USV navigation, the location of the obstacle ship is divided into four collision avoidance zones according to the International Regulations for Preventing Collisions at Sea (COLREGS). To obtain an improved DRL algorithm, the artificial potential field (APF) algorithm is utilized to improve the action space and reward function of the DQN algorithm. A simulation experiments is utilized to test the effects of our method in various situations. It is also shown that the enhanced DRL can effectively realize autonomous collision avoidance path planning.

Large-Scale State and Evolution of the Atmosphere and Ocean during PISTON 2018

AbstractThe Propagation of Intraseasonal Tropical Oscillations (PISTON) experiment conducted a field campaign in August–October 2018. The R/V Thomas G. Thompson made two cruises in the western North Pacific region north of Palau and east of the Philippines. Using select field observations and global observational and reanalysis datasets, this study describes the large-scale state and evolution of the atmosphere and ocean during these cruises. Intraseasonal variability was weak during the field program, except for a period of suppressed convection in October. Tropical cyclone activity, on the other hand, was strong. Variability at the ship location was characterized by periods of low-level easterly atmospheric flow with embedded westward propagating synoptic-scale atmospheric disturbances, punctuated by periods of strong low-level westerly winds that were both connected to the Asian monsoon westerlies and associated with tropical cyclones. In the most dramatic case, westerlies persisted for days during and after tropical cyclone Jebi had passed to the north of the ship. In these periods, the sea surface temperature was reduced by a couple of degrees by both wind mixing and net surface heat fluxes that were strongly (~200 W m−2) out of the ocean, due to both large latent heat flux and cloud shading associated with widespread deep convection. Underway conductivity–temperature transects showed dramatic cooling and deepening of the ocean mixed layer and erosion of the barrier layer after the passage of Typhoon Mangkhut due to entrainment of cooler water from below. Strong zonal currents observed over at least the upper 400 m were likely related to the generation and propagation of near-inertial currents.

Mitigation of CO2 emissions from international shipping through national allocation

Neither international treaties nor domestic policies control carbon dioxide (CO2) emissions from international shipping. To enhance mitigation, a new multilateral mechanism could allocate these emissions to national carbon budgets, where different options could be used based on the location of industry actors and ships. We analyze five allocation options, showing that a clear majority of CO2 emissions would be distributed to ten countries under each option; however, the top ten countries vary across allocation options and the amount of CO2 emissions allotted to individual countries could increase their carbon budgets thousand-fold or more. We further examine how the different objectives, principles for decision-making, and geographical coverage of the United Nations Framework Convention on Climate Change (UNFCCC) and the International Maritime Organization influence the design and implementation of an allocation mechanism under each of these two bodies. We find that the allocation mechanism that best meets criteria related to effectiveness and equity would be one in which emissions are assigned to countries of ship owners, and which operates under the UNFCCC.

Numerical simulation of seismic wave triggered by low-frequency sound source with 3D staggered-grid difference method in shallow water

Ship seismic wave is often used for targeting ship location. This elastic wave that traveled in the seabed layer is triggered by low-frequency ship noise. At present, most of the theoretical studies of ship seismic wave were conducted in the frequency domain and the wave components such as P-wave, S-wave, and normal mode wave cannot be distinguished. In this study, the propagation characteristics were studied by numerical simulation in the time domain based on 3D staggered-grid finite difference method whose availability was firstly verified through a theoretical solution. The numerical simulation results show that seismic waves in the seabed layer were dominated by transmitted S-wave and interface wave in the near-field area, and transmitted P-wave is not obvious here, while seismic waves were dominated by normal mode and interface wave in the far-field area, and when the sound source is moved away from the seafloor, the amplitude of normal mode wave becomes larger, but the amplitude of interface wave becomes smaller.

Detection of NO2 pollution plumes from individual ships with the TROPOMI/S5P satellite sensor

This paper presents an analysis of tropospheric NO2 column measurements from the TROPOspheric Monitoring Instrument onboard the Copernicus Sentinel 5 Precursor satellite (TROPOMI/S5P) for an oceanic area in the central Mediterranean on 2 July 2018. The day and area were selected because of the stable and cloud-free weather conditions with low wind speeds throughout most of the area, while covering one of the busiest worldwide international shipping corridors. In addition, the area was affected by sunglint, i.e. sunlight that is directly reflected by the ocean surface waves to the satellite which greatly enhances the signal-to-noise ratio of the satellite observations. The satellite measurements reveal plume-like emission structures in tropospheric NO2 columns while automated identification signal (AIS) data of ship locations reveal a total of 185 ships in the area. Combined with information about wind speed and wind direction within 3 h prior to the TROPOMI/S5P overpass, the ship tracks can almost perfectly be aligned with the plume-like tropospheric NO2 structures. In addition, information about ship length and ship speed, combined with an analysis of ship tracks and ship position, reveal that nearly all emission plume-like tropospheric NO2 structures can be attributed to the largest ships, mostly container ships and crude oil tankers. Overall, our results show for the first time ever that NO2 emission plumes from ships can be detected and attributed to individual ships using satellite measurements, while also providing strong support for using satellite sunglint measurements.

ЩОДО НЕОБХІДНОСТІ УДОСКОНАЛЕННЯ МЕТОДУ КЛАСТЕРИЗАЦІЇ МАРШРУТІВ СУДЕН ЯК ПРОЦЕДУРНОГО МОДУЛЯ АВТОМАТИЗОВАНОЇ СИСТЕМИ ОБРОБКИ ДАНИХ У СИСТЕМІ ВИСВІТЛЕННЯ НАДВОДНОЇ ОБСТАНОВКИ

The article is devoted to the analysis of the existing method of clustering of ship routes within the exclusive sea (economic) zone from the standpoint of substantiation of its application or identification of ways to improve it for use in the surface lighting system in the interests of national security at the state border. The study found that the existing method of clustering ship routes can not be explicitly applicable for use in the surface lighting system as a procedural module of the automated data processing system, which would provide a sufficient level of reliability to detect signs of violations of border legislation within the exclusive maritime ( economic) zone. It is also established that the improvement of the method of clustering of routes of ships should address the following issues: definition of such types of approximation for the formation of continuous routes of individual ships, which would provide a sufficient level of reliability of the results on given experimental data sets. time; justification for the choice of such a number of experimental points of location of ships and directly a combination of points that would ensure a sufficient level of reliability of the conclusions formed; study of different metrics to establish the similarity of arbitrary routes of ships from the standpoint of ensuring unambiguous conclusions; adaptation of the proposed tools to the boundary initial conditions of the studied problem; adaptation of the method for the case of arbitrary complexity of the route of vessels; formation of such a method of constructing a reference route within the desired cluster, which would ensure the reproduction of the route in the form of a continuous trajectory