With the development of sensor technology, sensor nodes are increasingly being used in underwater environments. The strategy presented in this paper is designed to solve the problem of using a limited number of autonomous underwater vehicles (AUVs) to complete tasks such as data collection from sensor nodes when the number of AUVs is less than the number of target sensors. A novel classified self-organising map algorithm is proposed to solve the problem. First, according to the K-means algorithm, targets are classified into groups that are determined by the number of AUVs. Second, according to the self-organising map algorithm, AUVs are matched with groups. Third, each AUV is provided with the accessible order of the targets in the group. The novel classified self-organising map algorithm can be used not only to reduce the total energy consumption in a multi-AUV system, but also to give the most efficient accessible order of targets for AUVs. Results of simulations conducted to prove the applicability of the algorithm are given.

Naval maritime operations entail a permanent concern for safety, ensuring that all crew members receive the necessary information on time. This implies the existence of specific training for improving non-technical skills (NTS). This paper proposes that bridge resource management (BRM) may be determinant for the success of naval maritime operations. Through a literature review on NTS, maritime team training and BRM, the paper presents insights about the way the level of NTS, inherent to BRM, may be determinant for naval officers to operate in safety. We propose that human error may be minimised and safety maximised in military teams operating in the maritime environment through the implementation of an NTS training programme. The paper offers an insight into the importance of safety during maritime operations, focusing on recent international orientations about training requirements, proposing that implementing BRM will be pivotal for the future of the military navy context.

A dynamic collision avoidance algorithm via layered artificial potential field with collision cone (LAPF-CC) is proposed to overcome the shortcomings of the traditional artificial potential field method in dynamic collision avoidance. In order to reduce invalid actions for collision avoidance, the potential field is divided into four layers, and a collision cone with risk detection function is introduced. Relative distance and relative velocity are used as variables to establish the risk of collision, and a torque named ‘speed torque’ is constructed. Speed torque, attractive force and repulsive force work together to change the speed and heading of the unmanned surface vehicle (USV). Driving force and torque are controlled separately, which makes it possible for the LAPF-CC algorithm to be used for real-time collision avoidance control of underactuated USVs. Simulation results show that the LAPF-CC algorithm performs well in dynamic collision avoidance.

The lane-level map, which contains the lane-level information severely lacking in widely used commercial navigation maps, has become an essential data source for autonomous driving systems. The linking relations between lane-level map and commercial navigation map can facilitate an autonomous driving system mapping information between different applications using different maps. In this paper, an approach is proposed to build the linking relations automatically. The different topology networks are first reconstructed into similar structures. Then, to build the linking relations automatically, the adaptive multi-filter algorithm and forward path exploring algorithm are proposed to detect corresponding junctions and paths, respectively. The approach is validated by two real data sets of more than 150 km of roads, mainly highway. The linking relations for nearly 94% of the total road length have been built successfully.

The satellite constellation with automatic dependent surveillance-broadcast on-board is of great importance for air traffic surveillance due to its multiple advantages compared with traditional methods. Although some research has been conducted on satellite constellation design based on coverage performance, the findings cannot entirely satisfy all the requirements of air traffic surveillance owing to the lack of analysis on inter-satellite links and network transmission. This paper presents a novel design of a low earth orbit satellite constellation network to solve this problem. Based on the requirements of space-based surveillance, an evaluation model of constellation performance is proposed concerning coverage, link and transmission. The simulation results show that the evaluation model can reflect the performance of a satellite constellation network designed for a space-based surveillance system, and a 55-satellite constellation design scheme with fairly good performance can fulfil the function of global real-time air traffic surveillance.

In maritime search and rescue (SAR), commanders need to understand the task execution efficiency of each SAR unit in real time to improve the overall efficiency of SAR efforts. This study proposes a method to evaluate the progress of maritime SAR missions using automatic identification system (AIS) data. First, the positioning accuracy of the AIS data was improved according to the relationship between position, speed, and course. Second, the historical track of the SAR ship was used to generate the SAR completion area based on a line buffer algorithm. The SAR completion area and SAR mission area were then superimposed to determine the overall progress of the SAR mission. The proposed method has been deployed within the SAR software on-board Haixun01 (China's largest and most advanced large-scale cruise rescue ship) since 2017 and has played an important role in devising SAR strategies and tracking mission progress, during several SAR actions.

The bacterial foraging optimisation (BFO) algorithm is a commonly adopted bio-inspired optimisation algorithm. However, BFO is not a proper choice in coping with continuous global path planning in the context of unmanned surface vehicles (USVs). In this paper, a grid partition-based BFO algorithm, named AS-BFO, is proposed to address this issue in which the enhancement is contributed by the involvement of the A* algorithm. The chemotaxis operation is redesigned in AS-BFO. Through repeated simulations, the relative optimal parameter combination of the proposed algorithm is obtained and the most influential parameters are identified by sensitivity analysis. The performance of AS-BFO is evaluated via five size grid maps and the results show that AS-BFO has advantages in USV global path planning.

Indoor positioning systems have received increasing attention for supporting location-based services in indoor environments. Wi-Fi based indoor localisation has become attractive due to its extensive distribution and low cost properties. IEEE 802.11-2016 now includes a Wi-Fi Fine Time Measurement (FTM) protocol which can be used for Wi-Fi ranging between intelligent terminal and Wi-Fi access point. This paper introduces a framework of Wi-Fi FTM data acquisition and processing that can be used for indoor localisation. We analyse the main factors that affect the accuracy of Wi-Fi ranging and propose a calibration, filtering and modelling algorithm that can effectively reduce the ranging error caused by clock deviation, non-line-of-sight (NLOS) and multipath propagation. Experimental results show that the proposed calibration and filtering method is able to achieve metre-level ranging accuracy in case of line-of-sight by using large bandwidth. Estimation results also show that the proposed Wi-Fi ranging model provides an accurate ranging performance in NLOS and multipath contained indoor environment; the final positioning error is less than 2·2 m with a stable output frequency of 3 Hz.

The increase in the number of commercial flights highlights the need for air traffic to follow air procedures. Unfortunately, general aviation aircraft used for recreational purposes keep entering controlled and restricted airspace without obtaining permission from air traffic services. Given the safety and operational problems this could potentially cause, this paper examines the underlying reasons for these incidents occurring. In particular, it analyses airspace infringements between 2008 and 2017 involving general aviation flights that were recorded in airspace in which a large number of commercial flights also fly in Europe and America. The reports were analysed based on an initial assessment of their quality. Information was latent in the narrative and subsequently both qualitative (content analysis) and quantitative methods (descriptive statistics) of analysis were used. The analysis revealed that airspace infringements were related to the pilot's flight planning, that is, flight-route choice, navigation skills and communication, in addition to requirement to adhere to airspace procedure. The findings could be used by national authorities and flying clubs to promote safe flying in these regions.

This paper describes a method to determine global navigation satellite systems (GNSS) satellite orbits and clocks for advanced receiver autonomous integrity monitoring (ARAIM). The orbit and clock estimates will be used as a reference truth to monitor signal-in-space integrity parameters of the ARAIM integrity support message (ISM). Unlike publicly available orbit and clock products, which aim to maximise estimation accuracy, a straightforward and transparent approach is employed to facilitate integrity evaluation. The proposed monitor is comprised of a worldwide network of sparsely distributed reference stations and will employ parametric satellite orbit models. Two separate analyses, covariance analysis and model fidelity evaluation, are carried out to assess the impact of measurement errors and orbit model uncertainty on the estimated orbits and clocks, respectively. The results indicate that a standard deviation of 30 cm can be achieved for the estimated orbit/clock error, which is adequate for ISM validation.

A spoofing attack on a global navigation satellite system (GNSS) receiver is a threat to a significant community of GNSS users due to the high stakes involved. This paper investigates the use of slope based metrics for the detection of spoofing. The formulation of slope based metrics involves monitoring correlators along with tracking correlators in the receiver's channel, which are slaved to the prompt tracking correlator. In this study, using some candidate metrics, detectors have been formed through the analysis of simulated spoofing attacks. A theoretical variance of each metric has also been calculated as a reference for the threshold. A threshold is estimated using the measured variance from the clean signals, for specific false alarm rate. By using the measured threshold, detectors are formed based on slope metrics. These detectors have been tested using TEXBAT data. The results show that the differential slope metrics have good performance. The results have also been compared with some other techniques of spoofing detection.

To detect the abnormal behaviour of ships in the waters of any jurisdiction and to improve the safety of maritime navigation, the meshing-based method is adopted to obtain discrete trajectory data and a probabilistic directed graph model is established to obtain historical data from ships' AIS (automatic identification systems). The state statistical characteristics of each node in the ship probability map are obtained to detect the navigation state of the ship in real time. By predicting the normal navigation trajectory of the ship, it can be judged whether the ship has the potential to behave abnormally at some moment in the future. Simulation experiments were designed based on a maritime simulator platform. The experimental results indicate that the model can correctly predict abnormal behaviour by ships, including excessive speed and deviation from the channel or normal sailing mode.

Considering unobserved spatial-temporal interaction effects, this study proposes a Bayesian spatial-temporal interaction model for predicting economic loss from fishing boat collisions using 10-year (2004–2014) collision records from six different areas in the waters of Fujian, China. Results show strong spatial heterogeneity and correlation effects in fishing boat collisions, while the economic loss from boat collisions gradually decreases with the time trend. Collision time, collision location, visibility and the involvement of LNG/LPG/chemical-carrying ships show similar marginal effects on the economic loss for the two collision types: fishing boat collisions and collisions involving no fishing boats. Navigational status and the involvement of cargo ships exhibit much bigger effects in fishing boat collisions compared with collisions involving no fishing boat. Unlike collisions involving no fishing boat, fishing boat collisions are associated with reduced economic loss in poor weather conditions characterised by strong wind/waves because in Fujian waters additional safety measures are adopted for fishing boats in such conditions. The proposed model is useful for policymakers in adopting safety enhancement strategies to decrease the economic loss resulting from fishing boat collisions.

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.

In the process of composing a double-differenced positioning model, it is difficult to separate different frequency signals between code division multiple access (CDMA) systems, the single-difference ambiguity of the pivot satellite and phase differential inter-system biases (PDISBs). Hence it is difficult to calibrate in advance the bias between systems in order to build an inter-system model which only needs one pivot satellite. Based on analysis of the stability of PDISB parameters for non-overlapping frequency CDMA systems, this study adopts a particle filter to estimate the fractional part of the PDISBs (F-PDISBs) between the systems and proposes a particle filter-based inter-system positioning model. Results show that the F-PDISBs and code DISBs for the baselines with the same receiver types and some with different receiver types are rather stable over time and for these baselines it is feasible to use a particle filter to estimate the F-PDISB parameters in the initial stage. Having attained the F-PDISBs, the inter-system model can be constructed to improve positioning accuracy in complex operational environments.

Global satellite navigation systems (GNSS) are nowadays used in many applications. GNSS receivers experience limitations in receiving weak signals in a degraded environment. Hence, tracking weak GNSS signals is a topic of interest to researchers in this field. Different methods have been proposed to address this issue, each of which has advantages and disadvantages. In this paper, a method based on the vector tracking method is proposed for weak signal tracking. This method has been developed based on a strong Kalman filter instead of the extended Kalman filter used in conventional vector tracking methods. In order to adjust important parameters of this filter, the fuzzy method is used. The results of tests performed with both simulated data and real data demonstrate that the proposed method performs better than previous ones in weak signal tracking.

Avoidance of collisions at sea is crucial to navigational safety. In this paper, we use a distributed algorithm to communicate the entire collision avoidance trajectory information for each ship. In each communication, we suggest a new improvement function considering safety and efficiency to identify the avoidance ship in each cycle. Considering the nonlinear collision avoidance trajectory of ships, a new method for calculating the degree of danger using a velocity obstacle algorithm is proposed. Therefore, in each communication, each ship considers the avoidance behaviours of other ships in planning its avoidance trajectory. Additionally, we combine bi-criterion evolution (BCE) and the ant lion optimiser to plan the entire collision avoidance path. Three scenarios are designed to demonstrate the performance of this method. The results show that the proposed method can find a suitable collision-free solution for all ships.