The maritime domain is the most utilised environment for bulk transportation, making maritime safety and security an important concern. A major aspect of maritime safety and security is maritime situational awareness. To achieve effective maritime situational awareness, recently many efforts have been made in automatic anomalous maritime vessel movement behaviour detection based on movement data provided by the Automatic Identification System (AIS). In this paper we present a review of state-of-the-art automatic anomalous maritime vessel behaviour detection techniques based on AIS movement data. First, we categorise some approaches proposed in the period 2011 to 2016 to automatically detect anomalous maritime vessel behaviour into distinct categories including statistical, machine learning and data mining, and provide an overview of them. Then we discuss some issues related to the proposed approaches and identify the trend in automatic detection of anomalous maritime vessel behaviour.

This paper proposes a novel mechanism for the initial alignment of low-cost INS aided by GPS. For low-cost INS, the initial alignment is still a challenging issue because of the high noises from low-cost inertial sensors. In this paper, a two-stage Kalman Filtering mechanism is proposed for the initial alignment of low-cost INS. The first stage is designed for the coarse alignment. To solve the problems encountered by the general coarse alignment approach, an INS error dynamic accounting for unknown initial heading error is developed, and the corresponding observation equation, taking into account the unknown heading error, is also developed. The second stage is designed for the fine alignment, where the classical INS error dynamics based on small attitude error is used. Experimental results indicate that the proposed alignment approach can complete the initial alignment more quickly and more accurately compared with the conventional approach.

Positioning in the urban environment using GNSS is hampered by poor satellite availability due to signal obstruction created by both man-made and natural features of the urban environment. In addition, range measurement to satellites for positioning and for navigation is severely degraded by the multipath effect. The arrival and continuous enhancement of computerised geometric city models makes it possible to tackle these problems through modelling. In this paper description is given of a method for determining the local multipath environment, defined by the surfaces within a city model that will cause disruptive signal reflections to be presented to a receiver. An example simulation is performed, and graphical and numerical results are produced.

For maritime safety and security, vessels should be able to predict the trajectories of nearby vessels to avoid collision. This research proposes three novel models based on similarity search of trajectories that predict vessels' trajectories in the short and long term. The first and second prediction models are, respectively, point-based and trajectory-based models that consider constant distances between target and sample trajectories. The third prediction model is a trajectory-based model that exploits a long short-term memory approach to measure the dynamic distance between target and sample trajectories. To evaluate the performance of the proposed models, they are applied to a real automatic identification system (AIS) vessel dataset in the Strait of Georgia, USA. The models' accuracies in terms of Haversine distance between the predicted and actual positions show relative prediction error reductions of 40·85% for the second model compared with the first model and 23% for the third model compared with the second model.

The main routes of ships voluntarily completing meteorological observations across the North Atlantic are detected by the intensity of the geographical distribution of the voluntary ship observations. The routes are then analysed in order to assess the relative intensity of traffic, the seasonal changes and the trend over the years. This paper will provide a better understanding of the North Atlantic trades and the relationship among the different routes, allowing the identification of the busiest areas. A discussion over the impact of routing on the weather that a transoceanic ship can experience during its life is also provided.

A type of fixed integral interval sliding method for optimization-based alignment is proposed in this paper. The method is more reasonable and suitable than those in the references due to the appropriate treatment of the noise in the outputs of the Inertial Measurement Unit (IMU). The undesired sensor noise of sensors includes both random noise and bias. Our optimal alignment is based on an integrated form where the bias will be integrated during the process of alignment. In this respect, the length of the integrated data is a key factor in determining current attitude due to the ambivalent effect of integrating the sensor noise. If the length is too great the precision deteriorates due to the integration of bias. If the length is too small the precision also deteriorates because of the randomness of the noise. The validity of the method is verified by simulation and measured data.

Shoe mounted Inertial Measurement Units (IMU) are often used for indoor pedestrian navigation systems. The presence of a zero velocity condition during the stance phase enables Zero Velocity Updates (ZUPT) to be applied regularly every time the user takes a step. Most of the velocity and attitude errors can be estimated using ZUPTs. However, good heading estimation for such a system remains a challenge. This is due to the poor observability of heading error for a low cost Micro-Electro-Mechanical (MEMS) IMU, even with the use of ZUPTs in a Kalman filter. In this paper, the same approach is adopted where a MEMS IMU is mounted on a shoe, but with additional constraints applied. The three constraints proposed herein are used to generate measurement updates for a Kalman filter, known as ‘Heading Update’, ‘Zero Integrated Heading Rate Update’ and ‘Height Update’.

The first constraint involves restricting heading drift in a typical building where the user is walking. Due to the fact that typical buildings are rectangular in shape, an assumption is made that most walking in this environment is constrained to only follow one of the four main headings of the building. A second constraint is further used to restrict heading drift during a non-walking situation. This is carried out because the first constraint cannot be applied when the user is stationary. Finally, the third constraint is applied to limit the error growth in height. An assumption is made that the height changes in indoor buildings are only caused when the user walks up and down a staircase. Several trials were shown to demonstrate the effectiveness of integrating these constraints for indoor pedestrian navigation. The results show that an average return position error of 4·62 meters is obtained for an average distance of 1557 meters using only a low cost MEMS IMU.

The paper presents a weather routing algorithm utilising a multi-objective optimisation with constraints, namely the Multi-objective Evolutionary Weather Routing Algorithm (MEWRA). In the proposed approach weather route recommendations can be made simultaneously e.g. for passage time, fuel consumption and safety of passage by means of Pareto optimisation. The sets of criteria and constraints in the optimisation process are fully customisable. The algorithm handles static (time-independent) and dynamic (time-dependent) constraints e.g. forecasted high wind speed regions or customisable areas to be excluded from routing (e.g. due to piracy). The paper includes a description of MEWRA as well as examples of its usage for finding Pareto-optimal transoceanic ship routes.

The maritime transport industry is increasingly reliant on computing and communication technologies, and the need for cyber risk management of critical systems and assets on vessels is becoming critically important. In this paper, a comprehensive cyber risk assessment of a ship is presented. An experimental process consisting of assessment preparation activities, assessment conduct and results communication has been developed. The assessment conduct relies on a survey developed and performed by interviewing a ship's crew. Computational vulnerability scanning of the ship's Electronic Chart Display and Information System (ECDIS) is introduced as a specific part of this cyber security assessment. The assessment process presented has been experimentally tested by evaluating the cyber security level of Kobe University's training ship Fukae-maru. For computational vulnerability scanning, an industry-leading software tool has been used, and a quantitative cyber risk analysis has been conducted to evaluate cyber risks on the ship.

Multi-rotor Unmanned Aerial Vehicles (UAVs), although originally designed and developed for defence and military purposes, in the last ten years have gained momentum, especially for civilian applications, such as search and rescue, surveying and mapping, and agricultural crops and monitoring. Thanks to their hovering and Vertical Take-Off and Landing (VTOL) capabilities and the capacity to carry out tasks with complete autonomy, they are now a standard platform for both research and industrial uses. However, while the flight control architecture is well established in the literature, there are still many challenges in designing autonomous guidance and navigation systems to make the UAV able to work in constrained and cluttered environments or also indoors. Therefore, the main motivation of this work is to provide a comprehensive and exhaustive literature review on the numerous methods and approaches to address path-planning problems for multi-rotor UAVs. In particular, the inclusion of a review of the related research in the context of Precision Agriculture (PA) provides a unified and accessible presentation for researchers who are initiating their endeavours in this subject.

Nowadays GPS is widely used to monitor the ionosphere. However, the current results from ground-based GPS observations only provide some information on the horizontal structure of the ionosphere, and are extremely restricted in mapping its vertical structure. In this paper, tomography reconstruction technique was used to image 3D ionospheric structure with ground-based GPS. The first result of the 3D images of the ionospheric electron density distribution in South Korea has been generated from the permanent Korean GPS Network (KGN) data. Compared with the profiles obtained by independent ionosondes at or near the GPS receiver stations, the electron density profiles obtained by the GPS tomographic construction method are in better agreement, showing the validity of the GPS ionospheric tomographic reconstruction. It has also indicated that GPS-based 3D ionospheric mapping has the potential to complement other expensive observing techniques in ionospheric mapping, such as ionosondes and radar.

This paper proposes a novel sensor fusion approach using Ultra Wide Band (UWB) wireless radio and an Inertial Navigation System (INS), which aims to reduce the accumulated error of low-cost Micro-Electromechanical Systems (MEMS) Inertial Navigation Systems used for real-time navigation and tracking of mobile robots in a closed environment. A tightly-coupled model of INS/UWB is established within the integrated positioning system. A two-dimensional kinematic model of the mobile robot based on kinematics analysis is then established, and an Auto-Regressive (AR) algorithm is used to establish third-order error equations of the gyroscope and the accelerometer. An Improved Adaptive Kalman Filter (IAKF) algorithm is proposed. The orthogonality judgment method of innovation is used to identify the “outliers”, and a covariance matching technique is introduced to judge the filter state. The simulation results show that the IAKF algorithm has a higher positioning accuracy than the KF algorithm and the UWB system. Finally, static and dynamic experiments are performed using an indoor experimental platform. The results show that the INS/UWB integrated navigation system can achieve a positioning accuracy of within 0·24 m, which meets the requirements for practical conditions and is superior to other independent subsystems.

In view that most Global Navigation Satellite System (GNSS) users are still using single-frequency receivers due to the low costs, single-frequency Precise Point Positioning (PPP) has been attracting increasing attention in the GNSS community. For a long period, single-frequency PPP technology has mainly relied on the Global Positioning System (GPS). With the recent revitalisation of the Russian GLONASS constellation and two newly emerging constellations, BeiDou and Galileo, it is now feasible to investigate the performance of Four-Constellation integrated Single-Frequency PPP (FCSF-PPP) with GPS, GLONASS, BeiDou and Galileo measurements. In this study, a FCSF-PPP model is presented to simultaneously process observations from all four GNSS constellations. Datasets collected at 47 globally distributed four-system Multi-GNSS Experiment (MGEX) stations on seven consecutive days and a kinematic experimental dataset are employed to fully assess the performance of FCSF-PPP. The FCSF-PPP solutions are compared to GPS-only and combined GPS/GLONASS single-frequency PPP solutions. The results indicate that the positioning performance is significantly improved by integrating multi-constellation signals.

The known navigational systems in use perform information functions and as such are helpful in the process of safe conduct of a vessel. One of the ways to assist in reducing the number of marine accidents is the development of systems which perform decision support functions, i.e. automatically generate solutions to collision situations. The use of information (and communication) technologies including knowledge engineering allows the generation of proposals for anti-collision manoeuvres taking into account the COLREGs. Demand for further enhancement of navigational safety by limiting human errors has initiated a trend to convert navigational information systems into decision support systems. The implementation of decision support systems will potentially reduce the number of human errors, which translates into a reduction of accidents at sea and their adverse consequences. This paper presents a summary of the research to date on the navigational decision support system NAVDEC. The system has been positively verified in laboratory conditions and in field tests – on a motor ferry and a sailing ship. Challenges associated with the development and implementation of such systems are outlined.

Autonomous ships are gaining in importance and are expected to shape the future of the global shipping industry. This evolutionary shift raises serious issues about compliance with the International Regulations for Preventing Collisions at Sea 1972 (COLREGs). This paper reviews the literature on autonomous ships from the perspective of the obligations of good seamanship imposed by COLREGs. The authors conclude that to facilitate the introduction of autonomous ships, the application barriers presented by COLREGs need to be analysed. With this goal, this paper presents a perspective from navigational practice. Four nautical scientists and two deck officers were invited to give their opinions. The analysis indicates that COLREGs require further elaboration and amendments to eliminate uncertainty of interpretation. In particular, the paper highlights the need to amend the ‘look-out’ rule (COLREGs Rule 5) to permit look-out by ‘computer vision’ alone while, at the same time, preserving the distinction between vessels navigating in restricted visibility and in sight of one another.

A novel design of an integrated system using Synthetic Aperture Radar (SAR) image and Automatic Identification System (AIS) data is proposed in this paper for the purpose of identifying ships at sea. TerraSAR-X® (SpotLight mode) images and AIS data collected over Incheon Port (Korea) and Tokyo Bay (Japan) were used on different dates. Four main steps for integration of SAR and AIS based ships can be identified, namely: ‘Time Matching’ to retrieve the respective Dead Reckoning (DR) position of the ships at SAR image acquisition times; ‘Position Matching’ based on a nearest neighbourhood re-sampling method with compensation of position shift; ‘Size Matching’ and ‘Speed Matching’. Under each of the matching criteria, the measurement error in each of the matching criteria was found to be less than 20% and the SAR extracted ship's hull boundaries were presented on a screen to display the system results. The results of this study will contribute to the design a Near-Real-Time (NRT) operational system for ship detection, identification, and classification by SARs in different data acquisition modes over various geographical locations at different acquisition times. This novel integrated system design will provide a most important preliminary step towards integration based on ships' hull monitoring in order to recognize ‘friend’ and ‘foe’ ship targets over a huge oceanic region and would be useful for coast guards as an early warning system.

This paper describes an ionospheric correction technique for single frequency GPS measurements from satellites in low Earth orbit. The fractional total electron content (TEC) above the receiver altitude is obtained from global TEC maps of the International GPS Service network and an altitude dependent scale factor. By choosing a suitable effective height of the residual ionosphere, the resulting path delay for positive elevations is then computed from a thin layer approximation. The scale factor can be predicted from the assumption of a Chapman profile for the altitude variation of the electron density or adjusted as a free parameter in the processing of an extended set of single frequency measurements. The suitability of the proposed model is assessed by comparison with flight data from the Champ satellite that orbits the Earth at an altitude of 450 km. For the given test case, a 90% correction of the ionospheric error is achieved in a reduced dynamic orbit determination based on single frequency C/A-code measurements.

The main problem in bringing autonomy to any vehicle lies in the design of a suitable guidance law. For truly autonomous operation, the vehicle needs to have a reliable Navigation, Guidance and Control (NGC) system of which the guidance system is the key element that generates suitable trajectories to be followed. In this review paper, various guidance laws found in the literature and their relevance to autonomous underwater vehicles (AUVs) are discussed. Since existing guidance laws for underwater vehicles have emulated from tactical airborne missile systems, a number of approaches for the missile guidance systems are considered. Finally, potential guidance strategies for AUVs are proposed.

Since programmable electronic calculators were first employed in marine navigation, a variety of formulae has been used for calculating astronomical refraction. As the choice is wide, some formulae have been selected from commonly used reference sources and their accuracy and suitability examined. No attempt has been made to assess the validity of the selected formulae to represent astronomical refraction in practical circumstances. Accuracy comparisons have been made using the refraction algorithm proposed by Garfinkel – the standard adopted by the British and American Nautical Almanac Offices. New formulae are given that are simple and accurate, even over a wide range of temperature and pressure, and which for all practical purposes may be considered equivalent to the tables of refraction given in the Nautical Almanac.

The Automatic Identification System (AIS) is an integral element in vessel tracking. But what about ‘Satellite AIS’? Is Satellite AIS a viable, current and effective tool to assist in vessel tracking? This paper will present the basic premise of reception of AIS by Low Earth Orbit (LEO) satellites. It will identify the technical aspects, present practical applications of Satellite AIS and look at implications for global tracking of vessels.