We proposed an adaptive H-infinity Cubature Kalman Filter (AH∞CKF) to improve the navigation accuracy of a highly manoeuvrable unmanned aerial vehicle (UAV). AH∞CKF fuses the Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) measurements. Traditional state estimation filters like extended Kalman filters (EKF) and cubature Kalman filters (CKF) assume Gaussian noises. However, their performance degrades for non-Gaussian noises and system uncertainties encountered in real-world applications. Thus, designing filters robust to noise and distribution is crucial. AH∞CKF combines H∞CKF design with an added adaptive factor to adjust the state estimation covariance matrix according to measurements by exploiting the square root method to yield more numerically stable results (SrAH∞CKF). We conducted multiple dynamically rich flight tests to validate our claims using a UAV equipped with a commercially well-known GNSS solution. Results show that the SrAH∞CKF state estimation outperforms EKF and CKF methods on average by 90% in various statistical measures.

The voyage data recorder (VDR) is a data recording system that aims to provide all navigational, positional, communicational, sensor, control and command information for data-driven investigation of accidents onboard ships. Due to the increasing dependence on interconnected networks, cybersecurity threats are one of the most severe issues and critical problems when it comes to safeguarding sensitive information and assets. Cybersecurity issues are extremely important for the VDR, considering that modern VDRs may have internet connections for data transfer, network links to the ship's critical systems and the capacity to record potentially sensitive data. Thus, this research adopted failure modes and effects analysis (FMEA) to perform a cybersecurity risk assessment of a VDR in order to identify cyber vulnerabilities and specific cyberattacks that might be launched against the VDR. The findings of the study indicate certain cyberattacks (false information, command injection, viruses) as well as specific VDR components (data acquisition unit (DAU), remote access, playback software) that required special attention. Accordingly, preventative and control measures to improve VDR cybersecurity have been discussed in detail. This research makes a contribution significantly to the improvement of ship safety management systems, particularly in terms of cybersecurity.

Several studies have been conducted on collision avoidance (CA) and path planning for maritime autonomous surface ships (MASS) based on artificial potential field (APF) and electronic navigation chart (ENC) data. However, to date, accurate, highly efficient, and automatic modelling of complicated geometry environment potential fields (EPFs) has not been realised. In this study, an accurate EPF model is established using ENC data to describe different types of obstacles, navigable areas, and non-navigable areas. The implicit equations of complex polygons are constructed based on the R-function theory, and the discrete-convex hull method is introduced to realise the automatic modelling of EPF. Moreover, collaborative CA and obstacle avoidance (OA) experiments are designed and conducted in a simulated environment and based on the ENC data. The results show that the proposed EPF modelling method is accurate, reliable, and time-efficient even with numerous ENC data and complex shapes owing to the R-function representation for geometric objects and discrete-convex hull method. The combination of improved APF and EPF models is proven to be effective for CA and OA. This paper presents a practical EPF modelling approach for APF-based ship path planning.

In this paper, the well-known multiplicative extended Kalman filter (MEKF) is re-investigated for attitude estimation using vector observations. From the Lie group theory, it is shown that the attitude estimation model is group-affine and its error state model should be trajectory-independent. Moreover, with such a trajectory-independent error state model, the linear Kalman filter is still effective for large initialisation errors. However, the measurement model of the traditional MEKF is dependent on the attitude prediction, which is therefore trajectory-dependent. This is also the main reason why the performance of traditional MEKF is degraded for large initialisation errors. Through substitution of the attitude prediction related term with vector observations in the body frame, a trajectory-independent measurement model is derived for MEKF. Meanwhile, MEKFs with reference attitude error definition and with global state formulating on special Euclidean group have also been studied, with the main focus on derivation of the trajectory-independent measurement models. Extensive Monte Carlo simulations of spacecraft attitude estimation implementations demonstrate that the performance of MEKFs can be much improved with trajectory-independent measurement models.

This study investigates whether the International Safety Management (ISM) Code remains an effective regulatory tool for the shipping industry by analysing maritime accident statistics published for the last 32 years by the Korea Maritime Safety Tribunal, 24 years by the International Maritime Organization (IMO) and seven years by the European Maritime Safety Agency. For this purpose, the data were divided into four groups: pre-ISM Code, in-transit, post-1 and post-2 periods, and tested by multilateral comparative analysis. The results show that the Korean merchant fleet has no improvement over the periods, whereas the world merchant fleet has a continual decrease in serious casualties. This study confirmed a trend of maritime accidents in recent years: fewer in number but heavier in damage. Conclusively, the results suggest that IMO and decision-makers in the maritime industry must review the ISM Code again and seek solutions to achieve the goal of continual improvement, as specified in the code.

While quantum accelerometers sense with extremely low drift and low bias, their practical sensing capabilities face at least two limitations compared with classical accelerometers: a lower sample rate due to cold atom interrogation time; and a reduced dynamic range due to signal phase wrapping. In this paper, we propose a maximum likelihood probabilistic data fusion method, under which the actual phase of the quantum accelerometer can be unwrapped by fusing it with the output of a classical accelerometer on the platform. Consequently, the recovered measurement from the quantum accelerometer is used to estimate bias and drift of the classical accelerometer which is then removed from the system output. We demonstrate the enhanced error performance achieved by the proposed fusion method using a simulated 1D accelerometer precision test scenario. We conclude with a discussion on fusion error and potential solutions.

Transverse arrangement is one of the main methods used in the polar inertial navigation system (INS). In the traditional algorithm, the calculation of using the earth ellipsoid model is complex, while using the earth sphere model cannot satisfy a high-accuracy application. Therefore, an approach based on the virtual sphere model is proposed, which has been proved in simulation experiments to reduce the computational complexity and maintain the same accuracy as the ellipsoid algorithm, but its accuracy has not yet been proved in theory. Starting from the basic principles of the ellipsoid and virtual sphere model algorithm, this paper compares the key formulations of the two. Finally, it is proved that the two arrangements are actually the same.

Effective communication among seafarers is an important part of ship resource management. The improvement of effective internal communication among seafarers has an important impact on the improvement of work performance. This paper conducts an empirical study to determine which factors are related to the impact of seafarers’ communication on work performance. A questionnaire was designed to investigate 339 seafarers from different companies, different ship types and different ranks. The hypotheses were tested and analysed by five-point Likert scale, hierarchical regression analysis and path analysis. The findings of the study show that communication frequency and communication quality have a significant positive effect on performance. The effect of communication quality on performance is greater than the effect of communication frequency on performance. Two dimensions of team diversity – knowledge and skill diversity – have a significant positive impact on communication quality. Based on the questionnaire and relevant analysis, this paper puts forward some suggestions to improve the seafarer's work performance from the perspective of communication.

Ultra-rapid products have the advantage of being used in real-time positioning with no external connections. In this study, these products provided by the international GNSS Monitoring and Assessment System (iGMAS) for four global constellations (GPS, GLONASS, Galileo and BDS-3) were assessed in terms of service rate and accuracy in navigation. In this regard, a MATLAB-based in-house code solving the problem was developed for all possible combinations of the constellations. To explore the effectiveness of the iGMAS products, the same dataset has been also processed using GFZ rapid products. The results demonstrate that the GPS and Galileo solutions were substantially comparable to the rapid products concerning service rate and accuracy, but that the GLONASS and BDS-3 iGMAS products require some enhancements. In addition, the Galileo solution produced remarkably good results both individually and in combination. The GPS/GLONASS/Galileo/BDS-3 SPP solution generated a mean root mean square (RMS) error of 0 ⋅ 54 m horizontally and 0 ⋅ 89 m vertically. Thus, GPS-only, GLONASS-only, Galileo-only and BDS-3-only solutions were improved by 42%, 79%, 28% and 74% in 3D mean RMS error with the quad system solutions, respectively.