Standards IEC 62288:2014 and MSC.191(79) require information on the displays of shipboard navigation systems to be logically grouped, but only provide limited specification for this ‘logical’ criterion. Meanwhile, complex interfaces and information overload remain as major design issues, being connected to several maritime accidents. To address this matter, a three-phase study was conducted to develop a pattern to organise essential information on Radar and Electronic Chart Display and Information System (ECDIS) displays and their equivalent modules on integrated navigation systems and integrated bridge systems. The first phase involved identifying the information most essential for safe navigation using cognitive task analyses, equipment performance standards and frequency of use. The second phase involved a card-sorting experiment with seafarers (n = 63) to develop an initial grouping pattern for the identified essential information. The third phase involved validating the initial grouping pattern with a new sample of seafarers (n = 35). The result is a pattern to group 48 types of information on shipboard navigation displays into 13 groups. The paper details the selected methods and the findings, and provides implications for future research.

Wayfinding skills decay in old age, more so for wayfinding in an allocentric than an egocentric reference frame. This study investigates whether wayfinding deficits of schoolchildren mimic those of older adults. Schoolchildren were tested on two wayfinding tasks: one could only be mastered in an allocentric, and the other only in an egocentric reference frame. The results were compared with those from a previous study of young and older adults who had been tested on the same two wayfinding tasks. It was found that wayfinding performance improved somewhat from school age to young adulthood and that this improvement proceeded more or less in parallel for the allocentric and the egocentric tasks. It was further found that wayfinding performance decayed from young to older adulthood and that this decay was more dramatic for the allocentric than for the egocentric task. This pattern of findings does not support the hypothesis that the wayfinding performance of schoolchildren mimics that of older adults.

Recent progress in using real-time kinematic (RTK) positioning has motivated the exploration of its application due to its high accuracy and efficiency. However, poorly-observed satellite data will cause unfixed ambiguities and markedly biased solutions. A novel partial ambiguity resolution method, named the irrespective of integer ambiguity resolution (IIAR) model, is proposed and applied to improve the reliability of ambiguity resolution. The proposed method contains initial ambiguity resolution and irrespective of integer ambiguity processes. The initial ambiguity resolution process applies an iterative partial ambiguity resolution method to obtain an approximate solution. The irrespective of integer ambiguity process transforms the approximate solution to a high-precision solution. Experiments show that the approximate solution is unreliable when the initial ambiguity resolution process has small redundancy, and the proposed method can obtain better results for those cases. The IIAR method showed about a 40% improvement of multi-GNSS ambiguity success rate and about a 25% improvement of standard deviation. Therefore, these results show that the proposed IIAR method can improve the results of multi-GNSS RTK positioning significantly.

Strapdown inertial navigation systems are widely used in surface ships and warships. Although high-precision optical fibre inertial navigation systems are available, they have high cost and limited practicality. Therefore, they cannot replace the traditional platform inertial navigation systems in all ships. Hence, microelectromechanical system (MEMS)-based inertial sensors are widely used for robust navigation. Accurate and timely identification of sensor faults while ensuring stable navigation is a challenging task. This paper proposes a robust fault detection (FD) approach for a low-cost system that loosely integrates a strapdown inertial navigation system and the global navigation satellite system, where the integrated navigation state estimation provides high-accuracy output. A cubature Hi/H∞-optimised FD filter was designed for a nonlinear discrete time-varying system considering sensitivity to faults and robustness to disturbances. Furthermore, a threshold for FD was derived considering a compromise between the false alarm rate and fault diagnosis accuracy. Finally, the proposed method was validated through simulations using multiple noise distribution sensor data generated by a ship-manoeuvring simulator.

The Autonomous Navigation System (ANS) constitutes a critical key enabling technology required for operating Maritime Autonomous Surface Ships (MASS). To assure the safety of MASS operations, the effective identification of potential objects and target ships interacting with the own MASS is quintessential. This study proposes a systematic method to identify the items interacting with the own MASS. This method is based on a similar approach previously employed for the encountering items’ identification in robotics, which is customised herein for the MASS needs. The developed method is applied to a short-sea shipping MASS. The environmental features, agents and objects related to her navigation are identified and ranked based on the frequency of encounter and the potential collision consequences. The results demonstrate the ability of the method to identify additional items in comparison to Automatic Identification System based data. The interactions with the small ships are considered as the most critical, due to their potential accidental consequences and their exhibited high frequency of encounter. This study results are employed to support the ANS design and testing of the investigated ship.

Determination of calibration parameters is essential for the fusion performance of an inertial measurement unit (IMU) and odometer integrated navigation system. Traditional calibration methods are commonly based on the filter frame, which limits the improvement of the calibration accuracy. This paper proposes a graph-optimisation-based self-calibration method for the IMU/odometer using preintegration theory. Different from existing preintegrations, the complete IMU/odometer preintegration model is derived, which takes into consideration the effects of the scale factor of the odometer, and misalignments in the attitude and position between the IMU and odometer. Then the calibration is implemented by the graph-optimisation method. The KITTI dataset and field experimental tests are carried out to evaluate the effectiveness of the proposed method. The results illustrate that the proposed method outperforms the filter-based calibration method. Meanwhile, the performance of the proposed IMU/odometer preintegration model is optimal compared with the traditional preintegration models.

In an effort to add context to a classroom lesson on celestial navigation, we present a numerical adaptation of Captain T.H. Sumner's 1837 journey into St. George's Channel. The adaptation is programmed into a ‘live’ web-based map. This allows for a flexible and highly visual presentation that highlights two important topics in celestial navigation: the origin of the line of position and the scale of maps. Considerations driving the numerical adaptation are discussed, as is as an overview of a classroom lesson we have been using.

Distance measuring equipment (DME/DME) as the main reversionary method provides alternative positioning, navigation and timing (A-PNT) services for use during a Global Navigation Satellite System (GNSS) outage. Considering the geometry limitation of DME/DME, multi-DMEs with better geometry can be used to increase the accuracy and integrity performance of positioning. This paper discusses the opportunities and challenges related to use of multi-DMEs as an alternate source of positioning, navigation and timing. To support the performance for A-PNT, the basic idea is considering the existing installed equipment. In this paper, barometer altimeter and TACAN are used to help improve the performance of A-PNT provided by multi-DMEs both in accuracy and integrity. Based on the database of EUROCONTROL, the test results demonstrate that 79⋅7% of a reference area roughly matching with the continental European locations achieve RNP 1 using multi-DMEs when the DME measurement accuracy is 0⋅2 NM (95%). When the DME measurement accuracy is 0⋅1 NM (95%), 87⋅9% of the reference area can achieve RNP 1 using multi-DMEs. The usage of barometer/TACAN measurements aided multi-DMEs improves the performance of the accuracy and integrity monitoring.

The paper reviews the optimisation methods of the flight trajectory for airliners. In contrast to maritime navigation, where the shortest route (the orthodrome) is preferred, in air navigation, the brachistochrone is the optimal flight trajectory on the sphere or on the ellipsoid, considering the wind vector field (maximising the tail wind and minimising the head wind over the duration of the flight). The major impact of the wind on the flight trajectory results from the possible significant velocity at the normal cruise flight levels, which could reach 200 kts, or 40% of the aircraft true airspeed (TAS). Brachistochrone is independent of the flight performance optimisation (range versus speed), as computed by the flight management system. Whichever cost index (CI) is selected (and consequently, the cruise Mach number), the brachistochrone is the minimum time of flight trajectory at that target Mach number. In cruise flight, the minimum time of flight is also equivalent to the minimum fuel consumption. It concerns just the wind velocity field. All these qualify the brachistochrone as the greenest trajectory, the most fuel and emissions efficient solution relative to the atmosphere. The paper classifies the brachistochrone problems (2D, 3D and 4D brachistochrones, with or without flexible time of departure). Some numerical examples are provided. The overall optimal 4D trajectory considers many aspects, including safety, by minimisation of total costs and risks of the 4D trajectory.

To solve the problem of spacecraft attitude manoeuvre planning under dynamic multiple mandatory pointing constraints and prohibited pointing constraints, a systematic attitude manoeuvre planning approach is proposed that is based on improved policy gradient reinforcement learning. This paper presents a succinct model of dynamic multiple constraints that is similar to a real situation faced by an in-orbit spacecraft. By introducing return baseline and adaptive policy exploration methods, the proposed method overcomes issues such as large variances and slow convergence rates. Concurrently, the required computation time of the proposed method is markedly reduced. Using the proposed method, the near optimal path of the attitude manoeuvre can be determined, making the method suitable for the control of micro spacecraft. Simulation results demonstrate that the planning results fully satisfy all constraints, including six prohibited pointing constraints and two mandatory pointing constraints. The spacecraft also maintains high orientation accuracy to the Earth and Sun during all attitude manoeuvres.

For the path planning of autonomous underwater vehicles (AUVs) in the ocean environment, in addition to the planned path length and safe obstacle avoidance, it is also necessary to pay attention to the impact of ocean currents on the planned path. Therefore, this paper improves the original D* algorithm, and adds the obstacle cost item and the steering angle cost item as constraints on the basis of the original cost function, thus ensuring the navigation safety of the AUV. Considering that ocean currents have a greater impact on the energy consumption of AUVs, this paper establishes a cost model for the impact of ocean currents on AUV energy consumption and applies it to the D* path planning algorithm, so that AUVs can use ocean currents to reduce energy consumption, which can be seen through simulation experiments. The simulation results show that the improvement of the algorithm can plan an optimal energy consumption path.

To achieve autonomous all-day flight by high-altitude long-endurance unmanned aerial vehicle (HALE UAV), a new navigation method with deep integration of strapdown inertial measurement unit (SIMU) and triple star sensors based on atmospheric refraction correction is proposed. By analysing the atmospheric refraction model, the stellar azimuth coordinate system is introduced and the coupling relationship between attitude and position is established. Based on the geometric relationship whereby all the stellar azimuth planes intersect on the common zenith direction, the sole celestial navigation system (CNS) method by stellar refraction with triple narrow fields of view (FOVs) is studied and a loss function is built to evaluate the navigation accuracy. Finally, the new SIMU/triple star sensors deep integrated navigation method with refraction correction upgraded from the traditional inertial navigation system (INS)/CNS integrated method can be established. The results of simulations show that the proposed method can effectively restrain navigation error of a HALE UAV in 24 h steady-state cruising in the stratosphere.

Remote monitoring and control systems are being used with more frequency, but the characteristics of situational awareness and decision-making from remote locations are largely unknown. Remote operators’ sources of information differ from on-board sources greatly in terms of perspective, field of view, and available data type (qualitative or quantitative). This study focused on clarifying the cognitive effects of first- and third-person perspectives on ship handling. A working hypothesis was formulated based on the findings of visual information processing and previous studies and tested using a developed ship handling simulator. The results revealed that: (1) the cognitive characteristics of the first-person perspective make it more effective in safely guiding ship handling than does the third-person perspective, and (2) the deviation in cognitive characteristics is prominent where collision can be easily avoided. The findings will aid the development of on-board and remotely piloted vessels and ensure the safety of their crews.

This paper proposes a novel speed optimisation scheme for unmanned sailboats by sliding mode extremum seeking control (SMESC) without steady-state oscillation. In the sailing speed optimisation scheme, an initial sail angle of attack is first computed by a piecewise constant function in the feed forward block, which ensures a small deviation between sailing speed and the maximum speed. Second, the sailing speed approaches to maximum gradually by extremum search control (ESC) in the feedback block. In SMESC without steady-state oscillation, a switching law is designed to carry out the control transformation, so that the speed optimisation system carries out SMESC in the first convergence phase and ESC without steady-state oscillation in the second stability phase. This scheme combines the advantages of both control algorithms to maintain a faster convergence rate and to eliminate steady-state oscillation. Furthermore, the strict stability of the speed optimisation system is proved in this paper. Finally, we test a 12-m mathematical model of an unmanned sailboat in the simulation to demonstrate the effectiveness and robustness of this speed optimisation scheme.