As part of an investigation into the difference of absolute sea-level across the English Channel, a detailed series of measurements of currents at all depths was recently made in the Strait of Dover. The main object of the measurements was to relate the residual non-tidal flow of water to the voltage on a cross-channel cable generated by electromagnetic effects. Over 6000 readings of current strength and direction were made during ideally calm conditions. This paper describes the results of analysis of these measurements, which covers vertical current profiles and tidal components, besides the non-tidal flow. Distinction is made between mean current measured at a fixed depth or at the surface, and the mean volume flux of water which involves tidal variation of depth. A method of tidal analysis based on Fourier sums, which is convenient for use with an electronic computer, is outlined in the Appendix.

This study examines maritime routes between ports along the Atlantic coast of the US, utilising Automated Identification System (AIS) data for the years 2010 through 2012. The delineation of vessel routes conducted in this study was motivated by development planned for offshore Wind Energy Areas (WEAs) along the Atlantic coast of the US and the need to evaluate the effect of these development areas on commercial shipping. To this end, available AIS data were processed to generate commercial vessel tracks for individual vessels, though cargo vessels are the focus in this study. The individual vessel tracks were sampled at transects placed along the Atlantic coast. The transect samples were analysed and partitioned by voyages between Atlantic ports to facilitate computation of vessel routes between ports. The route boundary analysis utilised a definition from UK guidance in which routes' boundaries encompassed 95% of the vessel traffic between ports. In addition to delineating route boundaries, we found multi-modal transverse distributions of vessels for well-travelled routes, which indicated preference for lanes of travel within the delineated routes.

This paper presents results from a doctoral dissertation (reference 12), on the problem of scheduling with Maximum Position Shift (MPS) constraints. The problem typically arises in a queueing system, when the service rate depends on the sequence in which customers are handled by the server. Such a queueing system is the airport runway system, where it has been shown (references 3, 10, 12) that rearranging the sequence of landings and takeoffs affects the runway capacity – that is, the rate of runway operations. An optimal Dynamic Programming (DP) scheduling algorithm is developed that takes as input the set of currently known flights, their desired time of operation, basis of the First Come First Served (FCFS) sequence, and a matrix of Air Traffic Control (ATC) minimum time separations, in order to produce an optimal schedule defined as runway and threshold time assignments maximizing runway capacity.

For multi-Autonomous Underwater Vehicle (multi-AUV) system task assignment and path planning, a novel Glasius Bio-inspired Self-Organising Map (GBSOM) neural networks algorithm is proposed to solve relevant problems in a Three-Dimensional (3D) grid map. Firstly, a 3D Glasius Bio-inspired Neural Network (GBNN) model is established to represent the 3D underwater working environment. Using this model, the strength of neural activity is calculated at each node within the GBNN. Secondly, a Self-Organising Map (SOM) neural network is used to assign the targets to a set of AUVs and determine the order of the AUVs to access the target point. Finally, according to the magnitude of the neuron activity in the GBNN, the next AUV target point can be autonomously planned when the task assignment is completed. By repeating the above three steps, access to all target points is completed. Simulation and comparison studies are presented to demonstrate that the proposed algorithm can overcome the speed jump problem of SOM algorithms and path planning in the 3D underwater environments with static or dynamic obstacles.

In this paper, by T. Degré and X. Lefèvre of the Organisme de Recherches Informatiques et Opérationnelles appliqués à la Navigation (ORION), the authors outline the principles of a proposed collision avoidance aid based on the concept of a ship's ‘room to manoeuvre’ in the presence of the vessels' or hazards to navigation and a corresponding bridge display.

Marine accident analysis is a sophisticated and complex official interpretation that requires a professional and fair judgment. For accidents such as a collision, contact and other incidents in the maritime field, the judgment mechanism of the courts depends on the decision process of the field experts. Field experts define the “Fraction Defectives” (FDs) of the vessels for the intended case based on the existing evidence and navigational specifications. However, evaluation of human judgment can be limited and problematic in analysing many aspects of a case. In this paper, a pairwise comparison method is used to simplify and clarify the judgment process. We aim to assess marine accidents in a stepwise approach that is inaccurately carried out in a holistic perspective by the field experts. A real accident that occurred in the past is simulated in front of the field experts. After conducting an expert consultation, FDs are re-calculated to compare both the regular judgment and the results in our suggested Generic Fuzzy Analytical Hierarchy Process (GF-AHP) approach.

The paper introduces a new approach to displaying information on targets. The proposed display visualises three types of information: targets' motion parameters (typical for target tracking), combinations of own course and speed which collide with those targets (typical for Collision Threat Parameters Area display by Lenart (1983)) and combinations of own course and speed which are not compliant with COLREGS in this case (based on ships' motion parameters and visibility conditions). A superposition of the last two types of data enables a navigator to quickly choose a collision avoidance manoeuvre which is both sufficient and COLREGS-compliant. Additionally, the displayed data may be filtered based on the remaining Time To Collision (TTC) so that navigators can concentrate on direct threats. The paper includes a description of the proposed visualisation technique as well as examples of visualised data for some encounter situations.

Domain analysis has a well-documented history in peer reviewed academic literature; however there are few instances of its application to facilitate the assessment of system specific navigation risk. This paper details one example of a practical approach to domain analysis for a busy section of the River Thames in Central London. The results correlate well to known high risk collision areas on the river and help to quantify and corroborate expert opinion and local knowledge. However a number of conditions must be accounted for in undertaking a robust study such as the geography of the study site, the purpose and audience of the research, and the availability of data and its limitations.

A review of existing knowledge regarding how to manage ice during offshore work in cold waters has been carried out. The objective has been to contribute to increased safety and efficiency in future projects by learning from world-wide experiences. It was found that offshore drilling has been carried out in a wide range of ice conditions and at water depths spanning from five metres to more than a thousand metres. Icebergs in open waters have been handled safely over several years and the possibility of detecting icebergs is considered good. With respect to icebergs frozen in sea ice, both detection and deflection is considered difficult and the technology for doing so is not proven. Good ice management systems are considered to represent the main factors for operating successfully in the covered waters. Future work should focus on how to include the effect of ice management statistically in a design process.

The modelling of most Global Navigation Satellite System (GNSS) errors/biases and developments of data processing techniques have been improved substantially since the birth of Global Positioning System (GPS), however, there has been much less progress in the improvement of phase multipath mitigation techniques. Multipath therefore remains one of the most important error sources in high precision GNSS positioning. This is because multipath is site-dependent and therefore cannot be eliminated by differencing techniques. Also multipath is highly dependent on satellite-reflector-antenna geometry, which usually causes rapid changes in phase multipath errors especially in Real-Time Kinematic (RTK) applications. Multipath mitigation for static antennas such as those at reference stations can be carried out by site calibration, averaging over long observation times, and through the estimation of the error using filtering based on signal-to-noise ratio (SNR) data. However, multipath mitigation for kinematic antennas is still very difficult today.

Nevertheless, much research has been carried out on a particular class of phase multipath mitigation techniques: ones that can be applied within positioning algorithms (rather than incorporated into the receiver tracking loops or antennas). This paper investigates and further develops a number of state-of-the-art techniques in this category. They include phase multipath estimation using SNR data, phase multipath estimation through the use of closely spaced antennas, multipath mitigation stochastic models such as the satellite elevation angle model and SNR-based models (SIGMA-∊ model and our modified SNR-based model), and our own novel ray-tracing method. The techniques are tested with both real and simulated data, the real test datasets have been collected on the Laboratoire Central des Ponts et Chaussées (LCPC) testbed near Nantes in France, and on the campus of the University of Nottingham during SPACE data collection experiments.

A region tracking fault tolerant control approach based on backstepping technique is proposed for Autonomous Underwater Vehicles (AUV). The proposed approach aims at driving tracking error to reach into the desired region in presence of ocean current disturbance, modelling uncertainty, unknown thruster faults and thruster amplitude and rate saturation constraints. At first, a type of piecewise and differential Lyapunov function is constructed to achieve region tracking control in the frame of backstepping technique. Then, the paper analyses and acquires the bound structures of the lumped uncertainty (including ocean current disturbance and model uncertainty) and the variation of thruster distribution matrix caused by unknown thruster faults, respectively. An adaptive technique is used to estimate the unknown coefficients in the above bound structures. In addition, an adaptive adjustment scheme for the desired trajectory is developed to achieve region tracking control with thruster amplitude and rate saturation constraints. The stability of the closed-loop system is analysed based on Barbalat's lemma. Finally, simulations and pool-experiments are presented to illustrate the effectiveness of the proposed method.

This paper focuses on depth trajectory tracking control for a Remotely Operated Vehicle (ROV) with dead-zone nonlinearity and saturation nonlinearity of thruster; an adaptive sliding mode control method based on neural network is proposed. Through the analysis of dead-zone nonlinearity and saturation nonlinearity of thruster, the depth trajectory tracking control system model of a ROV which uses thruster control signals as system input has been established. According to the principle of sliding mode control, an adaptive sliding mode depth trajectory tracking controller is built by using three-layer feed-forward neural network for online identification of unknown items. The selection method and update laws of the control parameters are also given. The uniform ultimate boundedness of trajectory tracking error is analysed by Lyapunov theorem. Finally, the effectiveness of the proposed method is illustrated by simulations.

The aim of the Integrated Navigation System (INS) on a ship bridge should be to provide the navigator with added value and aid in the complex task of conducting a safe and efficient passage at high speeds in demanding waters. This article presents a method for analysing eye tracking data to reveal sub-optimal design in the bridge layout and in the software graphical user interface on a maritime navigation display. The analysis of eye tracking data with a focus on scan path events indicates sub-optimal design, and the paper provides suggestions for improvement in design and interfaces. Pros and cons of using Eye Tracking Glasses in a maritime environment are presented. The importance of not affecting the normal behaviour of the navigator by collecting data is stressed, and how the software should provide good visualisation and interpretation of the eye tracking data.

This paper describes the application of navigational ideas during a late stage of the Yorkshire Ripper investigation. The conclusions reached were irrevocably recorded before the ultimate facts were established by the arrest and conviction of the killer. The reader is invited to assess the degree of success of the method and to rework the data supplied according to his own navigational ideas. The suggestion is made that navigational concepts may become a valuable weapon in the field of crime investigation.

The performance of Global Navigation Satellite System (GNSS) and Micro-Electro-Mechanical System (MEMS)-based Inertial Navigation System (INS) integrated navigation is reduced during GNSS outages. To bridge the period during GNSS outages, a novel hybrid intelligent algorithm incorporating a Discrete Grey Predictor (DGP) and a Multilayer Perceptron (MLP) neural network (DGP-MLP) is proposed. The DGP-MLP is used to provide a pseudo-GNSS position to correct the INS errors during GNSS outages; the DGP uses the GNSS position information of the latest few moments to predict the position of future moments; in the process of DGP-MLP, the MLP is used to modify the prediction errors of DGP, and the MLP is improved by adding momentum terms and adaptively adjusting the learning rate and momentum factor. To evaluate the effectiveness of the proposed methodology, four GNSS outages in different cases over a real field test data were employed. The experimental results demonstrate that the proposed methodology can significantly improve positioning accuracy during GNSS outages.

An electronic navigational chart is a major source of information for the navigator. The component that contributes most significantly to the safety of navigation on water is the information on the depth of an area. For the purposes of this article, the authors use data obtained by the interferometric sonar GeoSwath Plus. The data were collected in the area of the Port of Szczecin. The samples constitute large sets of data. Data reduction is a procedure to reduce the size of a data set to make it easier and more effective to analyse. The main objective of the authors is the compilation of a new reduction algorithm for bathymetric data. The clustering of data is the first part of the search algorithm. The next step consists of generalisation of bathymetric data. This article presents a comparison and analysis of results of clustering bathymetric data using the following selected methods: K-means clustering algorithm, traditional hierarchical clustering algorithms and self-organising map (using artificial neural networks).

In dense urban areas, conventional Global Navigation Satellite Systems (GNSS) positioning can exhibit errors of tens of metres due to the obstruction and reflection of the signals by the surrounding buildings. By using Three-Dimensional (3D) mapping of the buildings, the accuracy can be significantly improved. This paper demonstrates the first integration of GNSS shadow matching with 3D-mapping-aided GNSS ranging. The integration is performed in the position domain, whereby separate ranging and shadow matching position solutions are computed, then combined using direction-dependent weighting. Two weighting strategies are compared, one based on the computation of ranging-based and shadow matching position error covariance matrices, and a deterministic approach based on the street azimuth. Using experimental data collected from a u-blox GNSS receiver, it is shown that both integrated position solutions are significantly more accurate than either shadow matching or 3D-mapping-aided ranging on their own. The overall Root Mean Square (RMS) horizontal accuracy obtained using covariance-based weighting was 6·1 m, a factor of four improvement on the 25·9 m obtained using conventional GNSS positioning. Results are also presented using smartphone data, where shadow matching is integrated with conventional GNSS positioning.

In this paper collision threat parameters such as the distance at closest point of approach and time to the closest point of approach are derived and analysed for special cases and features; collision criteria are analysed for limitations. A new collision threat parameter - time to safe distance - is proposed and its different applications to collision avoidance are presented. Time to safe distance can replace time to the closest point of approach, as it gives a safer time in a dangerous situation. It can be applied in Automatic Radar Plotting Aids (ARPAs) to detect dangerous objects and to display possible evasive manoeuvres.

Ionospheric plasma irregularities or bubbles, that are regions with depleted density, are generated at the magnetic equator after sunset due to plasma instabilities, and as they move upward they map along the magnetic field lines to low latitudes. To analyse the temporal and spatial evolution of the bubbles over Brazilian territory, the mapping of ionospheric plasma bubbles for the night of 17/18 March 2002 was generated using data collected from one GPS receiver array, and applying interpolation techniques. The impact on the performance of Global Navigation Satellites System (GNSS) and on the Space Based Augmentation System (SBAS) in the tropical regions of the GPS signal losses of lock and of the signal amplitude fades during ionospheric irregularities is presented.

This study develops an ordered probit model to evaluate the factors influencing two-ship collision severity using ten years’ ship collision accident data from Fujian sea areas. The model results show that the involvement of big ships has the largest impact in increasing the probability of a serious or very serious accident, followed by the involvement of fishing vessels. There will be a bigger probability of a serious accident if both ships involved in the collision are cargo ships. We found that the season of spring, poor visibility and night time periods are more likely to be factors in high severity levels of ship collision. The results also reveal that lookout failure plays a decisive role in increasing serious accident risk compared with other types of human errors. The results of this study may be beneficial for policy-makers in proposing efficient strategies to reduce the likelihood of serious ship collisions.