Receiver Autonomous Integrity Monitoring (RAIM) provides an integrity service for Global Navigation Satellite Systems (GNSS). The conventional RAIM algorithm is based on the assumption of a single fault and typically uses the forward-backward method, which is based on the w-test or correlation analysis methods, to exclude the faults. It is suitable for single fault detection and exclusion, while it can lead to inefficiency, can be misleading and can even fail in the exclusion of multiple faults. To solve this problem, an improved method based on consensus voting of the w-test and correlation analysis methods is presented. To verify the performance of the improved method, tests using Global Positioning System (GPS)/BeiDou System (BDS) data have been carried out in comparison with the conventional methods in terms of false and correct faults exclusion rate and computational complexity in the case of a different number of faults. Results show that the improved method has almost the same correct exclusion rate compared to the conventional RAIM in the case of a single fault. It is worth noting that the improved method has a higher correct exclusion probability and computational efficiency as well as a lower possibility of false exclusion in the case of multiple faults.

In this work, a new concentric circles detection method for object detection is proposed. It has been applied to the images of a commercial radar, captured with a Charge-Coupled Device (CCD) camera. The processing includes the detection of centres and concentric circles in the images and the identification of the radar scale. Several methods found in the literature have been applied and compared with our novel proposal for multiple concentric circles detection, called “Propagation Method based on Circular Regression”. This methodology has been validated with real radar images, proving its efficiency in obtaining the distance of any object to a marine vessel, with high accuracy and low computational cost, in real time. This system can not only be applied to most existing radars in the market by adjusting the parameters of each model but our proposal for concentric circle detection can be also applied to other sensing applications.

To achieve fast satellite selection for a multi-Global Navigation Satellite System (GNSS), thereby reducing the burden on a receiver's processing element and the cost of hardware, and improving the utilisation ratio of receiver signal channels, the relationship between the number of satellites and Geometric Dilution Of Precision (GDOP), the number of satellites selected and the computation time is analysed. A fast rotating partition algorithm for satellite selection based on equal distribution of the sky is proposed. The algorithm divides the satellite selection process into two parts: rough selection and detailed selection. Unhealthy satellites, according to a health identifier, and low elevation angle satellites with a large troposphere delay are eliminated during the rough selection process. During the detailed satellite selection process, the satellite sky is divided and rotated to match satellites based on the average angle distance between the satellite and central partition line. Static data from the International GNSS Service (IGS) station and dynamic data collected at China University of Mining and Technology were used to verify the algorithm, and the results demonstrated that an inverse matrix could be avoided to reduce computation complexity. Additionally, the new satellite selection algorithm has the merit that there is little effect on the computation when the selected satellites and number of satellites in the field increased. A single system of the Global Positioning System (GPS) and double system of GPS/Globalnaya Navigazionnaya Sputnikovaya Sistema (GLONASS) both passed the hypothesis test for each epoch. By including BeiDou Navigation Satellite System (BDS) data, data utilisation increased to more than 95% using the rotating partition algorithm. Also, the GDOP and positioning performance of a rotating partition algorithm and an optimal Dilution Of Precision (DOP) algorithm are compared in this paper, and the analysis result shows that both of the algorithms have only a small difference of GDOP and have comparable positioning performance.

Four on-road studies were conducted in the Clifton area of Nottingham, UK, aiming to explore the relationships between driver workload and environmental engagement associated with ‘active’ and ‘passive’ navigation systems. In a between-subjects design, a total of 61 experienced drivers completed two experimental drives comprising the same three routes (with overlapping sections), staged one week apart. Drivers were provided with the navigational support of a commercially-available navigation device (‘satnav’), an informed passenger (a stranger with expert route knowledge), a collaborative passenger (an individual with whom they had a close, personal relationship) or a novel interface employing a conversational natural language ‘NAV-NLI’ (Navigation Natural Language Interface). The NAV-NLI was created by curating linguistic intercourse extracted from the earlier conditions and delivering this using a ‘Wizard-of-Oz’ technique. This term describes a research experiment in which subjects interact with a computer system that they believe to be autonomous, but which is actually being operated or partially operated by an unseen human being. The different navigational methods were notable for their varying interactivity and the preponderance of environmental landmark information within route directions. Participants experienced the same guidance on each of the two drives to explore changes in reported and observed behaviour. Results show that participants who were more active in the navigation task (collaborative passenger or NAV-NLI) demonstrated enhanced environmental engagement (landmark recognition, route-learning and survey knowledge) allowing them to reconstruct the route more accurately post-drive, compared to drivers using more passive forms of navigational support (SatNav or informed passenger). Workload measures (the Tactile Detection Task (TDT) and the National Aeronautical and Space Administration Task Load Index (NASA-TLX)) indicated no differences between conditions, although SatNav users and collaborative passenger drivers reported lower workload during their second drive. The research demonstrates clear benefits and potential for a navigation system employing two-way conversational language to deliver instructions. This could help support a long-term perspective in the development of spatial knowledge, enabling drivers to become less reliant on the technology and begin to re-establish associations between viewing an environmental feature and the related navigational manoeuvre.

The acquisition of modern Global Navigation Satellite System (GNSS) signals may be difficult due to the presence of a secondary code. Indeed, short coherent integration times should be used without non-coherent integration, which implies a low sensitivity; or long coherent integration times should be used, requiring synchronisation with the secondary code and thus a full correlation, which implies a significant computational burden, especially for signals with long secondary codes such as the Galileo E5 signal. A third option that lies between the previous two is to perform a partial correlation using less than one secondary code period as input, however this is less efficient in terms of complexity than using an entire secondary code period, and the code's autocorrelation properties are completely changed. The authors recently proposed a method based on combining secondary code correlations, allowing the use of intermediate coherent integration times with the possibility to do non-coherent integrations, and the method was successfully applied to the Global Positioning System (GPS) L5 signal. This paper studies the application of the method to the Galileo E5 signal, compares it with the partial correlation method, and discusses the case where less than one secondary code period is used as an input

Maritime anomaly detection can improve the situational awareness of vessel traffic supervisors and reduce maritime accidents. In order to better detect anomalous behaviour of a vessel in real time, a method that consists of a Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and a recurrent neural network is presented. In the method presented, the parameters of the DBSCAN algorithm were determined through statistical analysis, and the results of clustering were taken as the traffic patterns to train a recurrent neural network composed of Long Short-Term Memory (LSTM) units. The neural network was applied as a vessel trajectory predictor to conduct real-time maritime anomaly detection. Based on data from the Chinese Zhoushan Islands, experiments verified the applicability of the proposed method. The results show that the proposed method can detect anomalous behaviours of a vessel regarding speed, course and route quickly.

The hydrodynamic interaction effects on a tug operating in close proximity to a larger vessel can result in dangerous situations for the tug. To date most studies have focussed on the interaction effects between the vessels when they are operating in parallel, which represent only one of many practical ship-assist manoeuvres. It is therefore necessary to investigate a wide range of tug-ship combinations to obtain a detailed understanding of these effects. This paper discusses the hydrodynamic interaction effects on a tug operating at various relative positions and drift angles to a larger ship, both moving together at the same forward speed. The hydrodynamic effects were determined using Computational Fluid Dynamics (CFD) simulations that were validated using captive model test data. The range of manoeuvres discussed in this paper provides a comprehensive overview of the hydrodynamic interaction effects on a tug enabling tug operators to identify safe operating envelopes for their vessels.

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.

The accuracy in an X-ray pulsar-based navigation system depends mainly on the accuracy of the pulse phase estimation. In this paper, a novel method is proposed which combines an epoch folding process and a cross-correlation method with the idea of “averaging multiple measurements”. In this method, pulse phase is estimated multiple times on the sampled subsets of arriving photons' time tags, and a final estimation is obtained as the weighted average of these estimations. Two explanations as to how the proposed method can improve accuracy are provided: a Signal to Noise Ratio (SNR)-based explanation and an “error-difference trade-off” explanation. Numerical simulations show that the accuracy in pulse phase estimation can be improved with the proposed algorithm.

This paper presents a taxonomy of human wayfinding behaviours. For the purposes of this paper, wayfinding is purposeful navigating in everyday life, in man-made environments, traversing an environment or aiming for an objective with which the individual is unfamiliar. The taxonomy is developed through a review of wayfinding literature from research and practice, user studies conducted specifically for this research and a process of thinking by designing. This taxonomy can also be applied to navigating in documents printed on paper and on-screen, but this paper concentrates on behaviours in environmental space. This taxonomy creates twelve categories of behaviour differentiated by the characteristics of the information that they use. The categories of behaviour are also separated into three groups: social, semantic and spatial. This paper briefly describes and gives examples of each of the categories of behaviour. This is followed by insights into the behaviours from user studies conducted by the author. (This paper borrows its title from Cohen, 2015).

Connected and Autonomous Vehicles (CAVs) have been researched extensively for solving traffic issues and for realising the concept of an intelligent transport system. A well-developed positioning system is critical for CAVs to achieve these aims. The system should provide high accuracy, mobility, continuity, flexibility and scalability. However, high-performance equipment is too expensive for the commercial use of CAVs; therefore, the use of a low-cost Global Navigation Satellite System (GNSS) receiver to achieve real-time, high-accuracy and ubiquitous positioning performance will be a future trend. This research used RTKLIB software to develop a low-cost GNSS receiver positioning system and assessed the developed positioning system according to the requirements of CAV applications. Kinematic tests were conducted to evaluate the positioning performance of the low-cost receiver in a CAV driving environment based on the accuracy requirements of CAVs. The results showed that the low-cost receiver satisfied the “Where in Lane” accuracy level (0·5 m) and achieved a similar positioning performance in rural, interurban, urban and motorway areas.

The control segment in satellite navigation systems is responsible for estimating satellite orbit and clock bias which is required for a reliable Position, Navigation and Timing (PNT) user service. Initial orbit determination is a crucial step which accounts for all unknowns/anomalous parameters such as satellite orbit manoeuvres, on board and receiver clock frequency variations and environmental effects. It is vital that the estimates of the orbits and clock are insensitive to these factors. In this paper, an initial orbit determination method is presented using existing robust methodology for estimation of initial satellite position and its propagation using a variant of the Kalman Filter (KF) which allows the initial position determination process to be independent of satellite and receiver anomalies. The derivation of this KF variant is presented. Preliminary results obtained from simulated data are shown. The said method is checked for robustness by comparing results obtained for a given satellite position data set with that from the conventional Kalman Filter. The conventional KF exhibits divergence due to anomalies which are eliminated by the use of the method presented in this paper.

In this paper, a novel Voronoi-Visibility (VV) path planning algorithm, which integrates the merits of a Voronoi diagram and a Visibility graph, is proposed for solving the Unmanned Surface Vehicle (USV) path planning problem. The VM (Voronoi shortest path refined by Minimising the number of waypoints) algorithm was applied for performance comparison. The VV and VM algorithms were compared in ten Singapore Strait missions and five Croatian missions. To test the computational time, a high-resolution, large spatial dataset was used. It was demonstrated that the proposed algorithm not only improved the quality of the Voronoi shortest path but also maintained the computational efficiency of the Voronoi diagram in dealing with different geographical scenarios, while also keeping the USV at a configurable clearance distance c from coastlines. Quantitative results were generated by comparing the Voronoi, VM and VV algorithms in 2,000 randomly generated missions using the Singapore dataset.

The control problem for a ship steering system with speed loss is discussed in this paper. Two methods are proposed to deal with the unknown bounded disturbance for a sliding mode controller applied to a nonlinear surface vessel heading control system. The system uncertainties caused by speed changes are taken as internal disturbances, while the wave moments are considered as external disturbances. A feedback linearization method is adopted to simplify the nonlinear system. An adaptive method and a Nonlinear Disturbance Observer (NDO) are proposed for course keeping manoeuvres and speed keeping in vessel steering and provide robust performance for time varying wave disturbance and actuator dynamics. Furthermore, the overall stability conditions of the proposed controllers are analysed by Lyapunov's direct method. Finally, simulation results using the characteristics of a naval vessel illustrate the effectiveness of the presented control algorithms.

In this paper, a novel algorithm of weighted k-means clustering with geodesic criteria is presented to generate a uniform database for a star sensor. For this purpose, selecting the appropriate star catalogue and desirable minimum magnitude and eliminating double stars are among the steps of the uniformity process. Further, Delaunay triangulation and determining the scattered data density by using a Voronoi diagram were used to solve the problems of the proposed clustering method. Thus, by running a Monte Carlo simulation to count the number of stars observed in different fields of view, it was found that the uniformity leads to a significant reduction of the probability of observing a large number of stars in all fields of view. In contrast, the uniformity slightly increased the field of view needed to observe the minimum number of required stars for an identification algorithm.

E-navigation poses significant challenges for shipping. The analysis of the legal norms in the International Regulations for Preventing Collisions at Sea (COLREGS) and court decisions supports the use of information technology on the bridge for the purpose of improving navigational safety. However, the current regulatory and standardisation requirements hamper the introduction of new information streams in navigational systems and remove the incentives for investment in navigation technology. The liability arising from navigational failures will remain on the employer of the crew irrespective of how the additional navigational information is provided to the navigational systems. The shipowner's liability may depend on the way information streams are provided to the ship only within the context of the Civil Liability Convention (CLC) 1992 and other similar pollution conventions where the characterisation of the navigational system as a navigational aid or an aid to navigation may decide the issue of liability. Research on the legal background of these terms underlines the need for a clear distinction between the two terms to be made. An interpretation is proposed which ensures that the CLC liability exception operates in accordance with the underlying legal requirements.

The technique of tracking a non-cooperative manoeuvring satellite is important for Space Situation Awareness (SSA). However, the classical extended Kalman filter cannot work successfully in this situation. Motivated by this problem, a novel Extended Kalman Filter with Input Detection and Estimation (EKF/IDE) method is proposed in this paper for tracking a non-cooperative satellite with impulsive manoeuvres. The impulsive manoeuvre is modelled as an unknown acceleration without any prior information. An unbiased minimum-variance input and state estimation method is introduced to estimate the manoeuvre acceleration. An approach based on the Mahalanobis distance of the manoeuvre estimate error is proposed for manoeuvre detection. With the impulsive manoeuvre being detected and estimated accurately, an adaptive extended Kalman filter is proposed to estimate the state of the target. An approach of covariance inflation is proposed to deal with the manoeuvre during the unobserved period. Simulations and Monte Carlo experiments are implemented to demonstrate the feasibility and validity of the proposed method. The results of simulations show that the proposed method can accurately detect and estimate unknown impulsive manoeuvres of a non-cooperative satellite. Through the compensation of the estimated manoeuvre, the estimation of position and velocity after the manoeuvre maintains the accuracy of the pre-manoeuvre period, demonstrating the robustness of the proposed method against unknown manoeuvres.

This paper first investigates the influencing factors of between-receiver Differential Inter-System Bias (DISB) between overlapping frequencies of the Global Positioning System (GPS), Galileo and the Quasi-Zenith Satellite System (QZSS). It was found that the receiver reboot and the type of observations may have an impact on DISBs. The impact of receiver firmware upgrades and the activation of anti-multipath filters are also investigated and some new results are presented. Then a performance evaluation is presented of tightly combined relative positioning for a short baseline with GPS/Galileo/QZSS L1-E1-L1/L5-E5a-L5 observations with the current constellations, in which the recently launched Galileo and QZSS satellites will also be included. It is demonstrated that when DISBs are a priori calibrated and corrected, the tightly combined model can deliver a much higher empirical ambiguity resolution success rate and positioning accuracy with respect to the classical loosely combined model, especially under environments where the observed satellites for each system are limited and only single-frequency observations are available. The ambiguity dilution of precision, bootstrapping success rate, and ratio values are analysed to illustrate the benefits of the tightly combined model as well.