Numerous applications, not only Earth-based, but also space-based, have strengthened the interest of the international scientific community in using Global Navigation Satellite Systems (GNSSs) as navigation systems for space missions that require good accuracy and low operating costs. Indeed, already successfully used in Low Earth Orbits (LEOs), GNSS-based navigation systems can maximise the autonomy of a spacecraft while reducing the burden and the costs of ground operations. That is why GNSS is also attractive for applications in higher Earth orbits up to the Moon, such as in Moon Transfer Orbits (MTOs). However, the higher the altitude the receiver is above the GNSS constellations, the poorer and the weaker are the relative geometry and the received signal powers, respectively, leading to a significant navigation accuracy reduction. In order to improve the achievable GNSS performance in MTOs, we consider in this paper an adaptive orbital filter that fuses the GNSS observations with an orbital forces model. Simulation results show a navigation accuracy significantly higher than that attainable individually by a standalone GNSS receiver or by means of a pure orbital propagation.

The Global Positioning System (GPS) has become widespread in many civilian applications. GPS signals are vulnerable to interference and even low-power interference can easily spoof GPS receivers. In this paper, two techniques are proposed based on correlators and adaptive filtering to diminish the effect of spoofing on GPS-based positioning. The suggested algorithms are implemented in the tracking loop of the receiver. As a first method, a high-resolution correlator is utilised to avoid big parts of the influence of interference. To improve the results, a multicorrelator technique is also employed. In the second method, an adaptive filter is used for estimating the parameters of authentic plus spoof signals. Interference elimination is performed by subtracting the estimated conflict effects from the measured correlation function. These techniques provide easy-to-implement quality assurance tools for anti-spoofing. As a primary step, in this article, the proposed algorithms have been implemented in a Software Receiver (SR) to prove the concept of idea in multipath-free environments.

This paper introduces a scheme for waypoint-based path-following control for an Unmanned Robot Sailboat (URS) in the presence of actuator gain uncertainty and unknown environment disturbances. The proposed scheme has two components: intelligent guidance and an adaptive neural controller. Considering upwind and downwind navigation, an improved version of the integral Line-Of-Sight (LOS) guidance principle is developed to generate the appropriate heading reference for a URS. Associated with the integral LOS guidance law, a robust adaptive algorithm is proposed for a URS using Radial Basic Function Neural Networks (RBF-NNs) and a robust neural damping technique. In order to achieve a robust neural damping technique, one single adaptive parameter must be updated online to stabilise the effect of the gain uncertainty and the external disturbance. To ensure Semi-Global Uniform Ultimate Bounded (SGUUB) stability, the Lyapunov theory has been employed. Two simulated experiments have been conducted to illustrate that the control effects can achieve a satisfactory performance.

A biologically inspired neurodynamics-based tracking controller of underactuated Autonomous Underwater Vehicles (AUV) is proposed in this paper. The proposed control strategy includes a velocity controller with biological neurons and an adaptive sliding mode controller. The biological neurons are embedded into the backstepping velocity controller to eliminate the sharp speed jumps commonly existing in vehicles due to tracking errors changing suddenly. The outputs of the velocity controller are used as the command inputs of the sliding mode controller, and the thruster control constraints problems that are commonly seen in the backstepping control of AUV are solved by the proposed controller. Simulation results show that the control strategy achieved success in smoothly tracking AUV position and velocity.

Rotation vector-based attitude updating algorithms have been used as the mainstream attitude computation algorithms for many years. The most popular methodology for designing the rotation vector algorithm is by leveraging multiple samples of gyro integrated angular rate measurements. However, it has been pointed out by many researchers that the attitude updating accuracy is limited when using the multiple samples rotation vector algorithms, especially when the platforms work under high rate manoeuvres. The third-, fourth-, fifth- and sixth-order Picard component solutions of the rotation vector differential equation are given in this paper. A new design methodology for rotation vector-based attitude updating algorithms is proposed. Different vibratory dynamics and high rate manoeuvre roller coaster experiments were conducted to validate the effectiveness of the new algorithm. The results demonstrate the high accuracy of the new algorithm compared with conventional coning correction methods. The proposed algorithm can also be used in high accuracy attitude computation of a post-processing system, especially when the output frequency of the gyro is limited.

Navigational error accounts for half of the accidents and serious incidents in close to shore maritime transport in Norway predominantly due to the rapidly changing weather conditions and the dangerous nature of the narrow inshore waters found along the Norwegian coast. This creates a dependence on Differential Global Positioning System (DGPS) use and any disruption to this service can lead to an increased accident rate. The aim of this paper is to research the jamming vulnerability of existing maritime receivers and to understand if an upgrade to a multi-constellation or multi-frequency receiver would improve system resilience. The novelty of this work is a comparison of jamming resilience between different combinations of multiple constellations (GPS and Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS)) and multi-frequency Global Navigation Satellite System (GNSS) signals. This paper presents results from GNSS jamming trials conducted in the northern part of Norway, confirming previous research and indicating that typical maritime GPS receivers are easy to jam and may produce erroneous positional information. Results demonstrate that the single frequency multi-constellation receivers offer better jamming resilience than multi-frequency (L1 + L2) GPS receivers. Further, the GLONASS constellation demonstrated a better resilience than GPS. Results demonstrate a known correlation between GPS L1 and L2 frequencies, as well as a probable over-dependence on GPS for signal acquisition, meaning that no signal can be received without GPS L1 present. With these limitations in mind, the authors suggest that the most economic update to the single frequency GPS receivers, currently used for maritime applications, should be multi-constellation GPS + GLONASS receivers. This solution is cheaper and it also offer better jamming resistance for close to shore navigation than dual frequency receivers.

To improve the efficiency of multiple Autonomous Underwater Vehicles (multi-AUV) cooperative target search in a Three-Dimensional (3D) underwater workspace, an integrated algorithm is proposed by combining a Self-Organising Map (SOM), neural network and Glasius Bioinspired Neural Network (GBNN). With this integrated algorithm, the 3D underwater workspace is first divided into subspaces dependent on the abilities of the AUV team members. After that, tasks are allocated to each subspace for an AUV by SOM. Finally, AUVs move to the assigned subspace in the shortest way and start their search task by GBNN. This integrated algorithm, by avoiding overlapping search paths and raising the coverage rate, can reduce energy consumption of the whole multi-AUV system. The simulation results show that the proposed algorithm is capable of guiding multi-AUV to achieve a multiple target search task with higher efficiency and adaptability compared with a more traditional bioinspired neural network algorithm.

Autonomous orbit determination of a navigation constellation is the process by which the orbit parameters of navigation satellites are autonomously calibrated onboard the satellites without the need for external aids. It commonly uses a satellite onboard data processing unit and a filtering method to process the measurements of inter-satellite ranges. The onboard data processing unit is the main module of autonomous navigation systems. In this paper, the two main factors that affect the accuracy of autonomous orbit determination for a navigation constellation are discussed first, and then a distributed onboard algorithm for autonomous orbit determination of navigation satellites is proposed. This method is based on a long-term ephemeris prediction and is suitable for the satellite hardware capability. The main feature of this method is that both the distributed computing method and an onboard analytical state transition matrix are used to process inter-satellite range measurements. One of the main advantages of this approach is high-speed computing since the amount of calculations needed is significantly less than that of the centralised computing method and those distributed methods that need to use an onboard numerical integrator. Another advantage of this approach is that the use of the onboard analytical state transition matrix algorithm can save a great amount of resources for both ground-to-satellite data transmissions and data storage units in satellites’ hardware. This could result in substantial cost reduction for space missions. Finally, a simulation method used for testing the proposed algorithm is presented. Results of tests over a period of 90 days show that the user range error of autonomous orbit determination derived from the proposed method is less than three metres.

Marine accident analysis is important for ships passing through narrow, shallow and busy waterways. This study analyses the accidents which have occurred in the Istanbul Strait and proposes both quantitative and qualitative assessments of marine accidents. Marine accidents occurring in the Istanbul Strait are analysed by using a method based on neuro-fuzzy and genetically optimised fuzzy classifiers. It can be concluded that accident severity increases when poor weather conditions prevail in the Strait regardless of ship size. Therefore, solutions to reduce unwanted events should be prioritised by accounting for weather conditions and the capacity of the vessels. This analysis indicates that the safety level would be significantly improved if all the vessels follow the passage guidelines.

Underwater position data is a key requirement for the navigation and control of unmanned underwater vehicles. The proposed navigation scheme can be used in any vessel or boat for any shallow water vehicle. This paper presents the position estimation algorithm developed for shallow water Remotely Operated Vehicles (ROVs) using attitude data and Doppler Velocity Log data with the initial position from the Global Positioning System (GPS). The navigational sensors are identified using the in-house developed simulation tool in MATLAB, based on the requirement of a position accuracy of less than 5%. The navigation system is built using the identified sensors, Kalman filter and navigation algorithm, developed in LabVIEW software. The developed system is tested and validated for position estimation, with an emulator consisting of a GPS-aided fibre optic gyro-based inertial navigation system as a reference, and it is found that the developed navigation system has a position error of less than 5%.

This paper presents a comparative cyber security resilience estimation of shipboard radars that are implemented on two oil/chemical tankers certified as SOLAS ships. The estimated radars were chosen from the same manufacturer, but belonged to different generations. The estimation was conducted by means of ships' crew interviews and computational testing of the radars using a widely deployed vulnerability scanning software tool. The identified cyber threats were analysed qualitatively in order to gain a holistic understanding of cyber risks threatening shipboard radar systems. The results obtained experimentally indicate that potential cyber threats mainly relate to maintenance of the radars' underlying operating system, suggesting the need for regulatory standardisation of periodic cyber security testing of radar systems.

With more and more missions around the Moon, a communication/navigation constellation around the Moon is necessary. Halo orbits, due to their unique geometry, are extensively studied by researchers for this purpose. A dedicated survey is carried out in this work to analyse the coverage ability of halo orbits. It is found that a two-satellite constellation is enough for continuous one-fold coverage of the north or the south polar regions but never both. A three-satellite constellation is enough for continuous one-fold coverage of both north and south polar regions. A four-satellite constellation can cover nearly 100% of the whole lunar surface. In addition, the coverage ability of another special orbit – distant retrograde orbit (DRO) – is analysed for the first time in this study. It is found that three satellites on DROs can cover 99·8% of the lunar surface, with coverage gaps at polar caps. A four-satellite constellation moving on spatial DROs can cover nearly the whole lunar surface. By combining halo orbits and DROs, we design a five-satellite constellation composed of three halo orbit satellites and two DRO satellites. This constellation can provide 100% continuous one-fold coverage of the whole lunar surface.

A planet centroid is an important observable object in autonomous optical navigation. A high-accuracy algorithm is presented to extract the planet centroid from its raw image. First, we proposed a planet segmentation algorithm to segment the planet image block to eliminate noise and to reduce the computation load. Second, we developed an effective algorithm based on Prewitt-Zernike moments to detect sub-pixel real edges by determining possible edges with the Prewitt operator, removing pseudo-edges in backlit shady areas, and relocating real edges to a sub-pixel accuracy in the Zernike moments. Third, we proposed an elliptical model to fit sub-pixel edge points. Finally, we verified the performance of this algorithm against real images from the Cassini-Huygens mission and against synthetic simulated images. Simulation results showed that the accuracy of the planet centroid is up to 0·3 pixels and that of the line-of-sight vector is at 2·1 × 10−5 rad.

Geometric Dilution Of Precision (GDOP) is a factor that describes the effect of geometry on the relationship between measurement error and position determination error. It is used to provide an indication of the quality of the solution. Conventional closed-form GDOP calculation formula applied to all possible combinations of visible satellites is rather time consuming, especially as the number of satellites grows. Approximations, such as the maximum volume method, are faster but optimum selection is not guaranteed. In this paper, a more concise but efficient solution for the calculation of GDOP value in the case of four Global Positioning System (GPS) satellites is firstly reviewed and then extended to cover the other forms of dilution of precision (DOP) values, including vertical DOP (VDOP) and horizontal DOP (HDOP). Secondly, a review and extension of the conventional solution is performed in the case of three GPS satellites aided by an altimeter. Based on the ideas gained from these two approaches, a simpler closed-form DOP formula for three GPS satellites aided by an altimeter is derived. The advantage of the proposed formulation is that it is simpler and thus reduces the computational load in comparison to the conventional one.

In this paper, a conventional Strapdown Inertial Navigation System (SINS) alignment method on a disturbed base is analysed. A novel method with an attitude tracking idea is proposed for the rocking base alignment. It is considered in this method that the alignment algorithm should track the rocking base attitude real changes in the alignment process, but not excessively restrain disturbance. According to this idea, a rapid alignment algorithm is devised for the rocking base. In the algorithm, coarse alignment is carried out within 30 s in the inertial frame with alignment precision less than 2°, which meets Kalman filter linearization conditions well. Then a Kalman filter with ten state vectors and four measurement vectors is applied for the fine alignment to improve the capability of the algorithm in tracking the vehicle attitude. A turntable rotation experiment is carried out to validate the capability of the fine algorithm in tracing the large magnitude change during alignment. It is shown that the repeated alignment precision is about 0·04° by the alignment experiment on a rocking vehicle, with alignment time of 180 s. The Laser Strapdown Inertial Navigation System (LINS) ground navigation experiment suggests that the algorithm proposed by this paper can be satisfied without the need of high precision SINS alignment.

As tugboats interact very closely with ships in restricted waters, the possibility of accidents increases in these operations. Despite the high accident possibility, there is a gap in studies on tugboat accidents. This study aims to analyse accidents involving tugboats using data mining. For this purpose, a tugboat accidents dataset consisting of a total of 496 accident records for the period from 2008 to 2019 was collected. Logistic regression and decision tree algorithms were implemented to the dataset. The results revealed that tugboat propulsion type is the most important and influential factor in the severity of tugboat accidents. The inferences drawn from these results could be beneficial for tugboat operators and port authorities in enhancing their awareness of the factors affecting tugboat accidents. In addition, the outputs of this study can be a reference for management units in developing strategies for preventing tugboat accidents and can also be used in effective planning for practicable prevention programmes and practices.

The Japanese Quasi-Zenith Satellite System (QZSS) is a regional satellite navigation system capable of transmitting navigation signals that are compatible and interoperable with other Global Navigation Satellite Systems (GNSS). In addition to navigation signals, QZSS also transmits augmentation signals, e.g. the L-band Experimental (LEX) signal. The LEX signal is unique for QZSS in delivering correction messages such as orbits and clock information that enable real-time Precise Point Positioning (PPP). This study aims to evaluate the availability of the LEX signal as well as the quality of the broadcast correction messages for real-time PPP applications. The system is tested in both static and kinematic positioning modes. The results show that the availability of the LEX signal is 60% when the QZSS satellite elevation is at 30° and above 90% when the satellite is above 40° elevation. Centimetre-level position accuracy can be obtained for static PPP processing after two hours of convergence using the current MADOCA-LEX (Multi-GNSS Advanced Demonstration of Orbit and Clock Analysis) correction messages transmitted on the LEX signal; and decimetre-level point positioning accuracy can be obtained for kinematic PPP processing.

One of the most important factors for the safety of navigation is to ensure proper collision avoidance manoeuvres in a congested traffic area. There are many aids for this purpose; for example, an ARPA, which is mandatory for certain ships and which is expected to be effective.

Navigation and positioning system users are demanding greater accuracy and reliability in ever more challenging environments. This is driving a wave of rapid innovation, with the result that multisensor integrated navigation systems will become much more complex. This introduces a number of problems, including how to find the necessary expertise to integrate a diverse range of technologies, how to combine technologies from different organisations that wish to protect their intellectual property, and how to incorporate new navigation technologies and methods without having to redesign the whole system. It also makes it desirable to share development effort over a range of different applications. To address this, the feasibility of a modular approach to the design and development of multisensor integrated navigation and positioning systems is analysed. Assessments of the requirements of different user communities and the adaptability of the different navigation and positioning technologies to different contexts and requirements are presented. Based on this, the adoption of an open interface standard for modular integration is recommended and the issues to be resolved in developing that standard are outlined.

The Faculty of Maritime Studies, University of Rijeka, Croatia, manages the European Union (EU) project “Avoiding Collisions at Sea” (ACTs). The project is funded by the European programme “Leonardo da Vinci”. Other maritime education and training institutions participating in this project come from Great Britain, Spain, Slovenia, Bulgaria and Turkey. The purpose of this research was to identify skill gaps in knowledge and teaching of COLREGs (International Regulations for Preventing Collisions at Sea 1972 - Rules) for nautical Bachelor of Science (BSc) students and experienced deck officers. The analysis of the research on marine accidents has identified vessel collisions as one of the most frequent types of accidents. Further research showed that human error and misinterpretation of the Rules are the most frequent reasons for vessel collisions. Using a questionnaire, nautical students/navigating cadets and navigating officers' understanding of the Rules was tested. The results showed skill gaps in understanding of some parts of the COLREGs due to wrong interpretation and application of the Rules. The authors claim that it is possible to improve the professional competence of navigating officers by applying proper learning methods using real-life scenarios and e-learning.