This paper presents a hybrid unscented particle filter (UPF) based on the firefly algorithm for tightly-coupled stereo visual-inertial vehicle positioning systems (VIVPS). Compared with standard UPF, this novel approach can achieve similar estimation accuracy with much less computational complexity. To reduce the computational complexity, the time updating of the hybrid unscented Kalman filter is conducted via the formula of standard linear Kalman filter on the basis of the constructed linear/nonlinear mixed filter model. The particle updating of the particle filter is optimised by modified firefly algorithm to reduce the number of particles needed by means of moving particles towards high likelihood regions via the attraction and movement of fireflies, leading to a significant reduction of computational complexity. Experimental results show the average execution time of the proposed approach is 23·8% that of the standard UPF with similar accuracy, indicating the designed method for tightly-coupled stereo VIVPS can better satisfy the real-time requirement of the system.

Facilitated by the establishment of terrestrial networks and satellite constellations of Automatic Identification System (AIS) receivers, large quantities of spatial and temporal information that trace ships' paths have been collected. The exponential increase in the amount of AIS data has caused expensive and time-consuming transmission, calculation and storage problems. Using appropriate trajectory simplification methods in a timely manner to compress redundant information while minimising the loss of importation information is important. To minimise the simplification error, this paper proposes an online multi-dimensional simplification algorithm for AIS trajectory streaming data. The simplification algorithm takes into account position, direction and speed preservation. Finally, a comparison experiment with other algorithms is made to examine the effectiveness of this algorithm. The results indicate that the proposed online multi-dimensional simplification algorithm can effectively preserve a ship's motion state, including its position, speed and course.

This paper analyses for the first time the impact of new GPS signals on positioning accuracy for dynamic urban applications, taking bus operations as an example. The performance assessment addresses both code measurement precision and positioning accuracy. The former is based on signal-to-noise ratio and estimation of multipath and noise by a combination of code and carrier phase measurements. The impact on positioning accuracy is derived by comparing the performance achievable with the conventional single frequency GPS only positioning both relative to reference trajectories from the integration of carrier phase measurements with data from a high grade inertial measurement unit. The results show that L5 code measurements have the highest precision, followed by L1 C/A and L2C. In the positioning domain, there is a significant improvement in two-dimensional and three-dimensional accuracy from dual frequency code measurements over the single frequency measurements, of 39% and 48% respectively, enabling more bus operation services to be supported.

A distributed four-dimensional (4D) trajectory generation method based on multi-agent Q learning is presented for multiple unmanned aerial vehicles (UAVs). Based on this method, each vehicle can intelligently generate collision-free 4D trajectories for time-constrained cooperative flight tasks. For a single UAV, the 4D trajectory is generated by the bionic improved tau gravity guidance strategy, which can synchronously guide the position and velocity to the desired values at the arrival time. Furthermore, to optimise trajectory parameters, the continuous state and action wire fitting neural network Q (WFNNQ) learning method is applied. For multi-UAV applications, the learning is organised by the win or learn fast-policy hill climbing (WoLF-PHC) algorithm. Dynamic simulation results show that the proposed method can efficiently provide 4D trajectories for the multi-UAV system in challenging simultaneous arrival tasks, and the fully trained method can be used in similar trajectory generation scenarios.

This paper proposes a framework to assess the influence of Offshore Wind Farms (OWFs) on maritime traffic flow based on raw Automatic Identification System (AIS) data collected before and after the installation of the offshore wind turbines. The framework includes modules for data acquisition, data filtering and statistical analysis. The statistical analysis characterises the influence of an OWF on maritime traffic in terms of minimum passing distances and lateral distribution of the ship trajectories near the OWF. The framework is applied to a specific route for which AIS data is available before and after an OWF installation. The impacts of the OWF on marine traffic are diverse and depend on the ship type categories. This paper quantitatively characterises an OWF's influence on a specific route that is probabilistically modelled, which is important for further studies on OWF site selection and maritime traffic risk assessment and management.

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.

Safety in ice-covered polar waters can be optimised via the choice of a ship's route. This is of utmost importance for conventional as well as autonomous ships. However, the current state of the art in e-Navigation tools has left two open questions. First, what essential information are these tools still missing, and second, how they are seen by sea captains. In order to address these questions, we organised an ice navigation workshop to systematically collect routing justifications given by and waypoints planned by experienced sea captains that are particularly seasoned in ice navigation. Here, we report the outcome of that workshop. Our key findings include the reasoning and the commentary of the participants in looking for a better and safer route. These comments shed light upon both the official and unofficial code of conduct in open waters and boil down into a list of additional prerequisite information if further steps towards system autonomy are sought. Finally, the expert-planned waypoints are to be published alongside this paper to act as a benchmark for future maritime studies.

Ship density is widely accepted as a basic and major indicator to reflect the marine traffic situation, but it has some limitations in representing the compactness and complexity of ship traffic. To overcoming these limitations, the paper proposes a novel ship density model based on the radial distribution function in molecular dynamics. The proposed model can identify the density and compactness of traffic around each ship and then map the ship density from a microscopic perspective. In addition, the proposed model can identify the global density and the complexity of ship traffic to some extent in the macroscopic perspective. Utilising case studies, the effectiveness of the proposed model is validated through the analysis of ship density in several regions in the Bohai Strait area. The proposed model is developed to help marine surveillance operators gain a better understanding of the traffic situation and to assist them in their work, eventually contributing to navigational safety.

Systematic error is one of the major factors that affect positioning accuracy owing to the changeable and complex nature of seawater environments. Based on a Global Navigation Satellite System-acoustic intelligent buoys system, whose acoustic array consists of a series of surface buoys, a single-difference method for underwater dynamic positioning is proposed to eliminate systematic error. Positioning configuration optimisation was addressed using dilution of precision (DOP). A simulation of DOP proved that for the single-difference method, a radiation network with a centre-difference reference point was superior to a regular polygon network. The positioning experiment showed that the novel method could effectively eliminate systematic error, improving vertical positioning accuracy from a metre- to a decimetre scale.

Map-matching is widely used in automotive navigation systems to locate vehicle positions on a given digital road map. Various map-matching algorithms have been developed focusing on different application needs. Within the Ghosthunter project, a weighting-function-based map-matching algorithm has been developed for detecting wrong-way driving in order to improve road safety, particularly in Autobahn entrance and exit areas. This paper aims at exploring the potential use of lane-level attributes and height data in improving the success rate of the previously presented algorithm. This algorithm performs well in entrance and exit areas to the Autobahn, with a high success rate of 99.5% in identifying the road on which the vehicle is actually travelling. In the enhanced algorithm presented in this paper the weight coefficients used for computing the total weighting score of candidate roads are adjusted with the aid of one or both kinds of these precise data. The results confirmed that the usage of these precise data can effectively help to detect and correct mismatches at junctions and overpasses.

In traditional Simultaneous Localisation and Mapping (SLAM) algorithms based on Extended Kalman Filtering (EKF-SLAM), the uncertainty of state estimation will increase rapidly with the development of the exploration process and the increase of map area. Likewise, the computational complexity of the EKF-SLAM is proportional to the square of the number of feature points contained in the state variables in a single filtering process. A new SLAM algorithm combining the local submaps and the body-fixed coordinates of the rover is presented in this paper. The algorithm can reduce the computational complexity and enhance computational speed in consideration of the processing capability of the onboard computer. Due to the introduction of local submaps, the algorithm represented in this paper is able to reduce the number of feature points contained in the state variables in each single filtering process. Therefore, the algorithm could reduce the computational complexity and improve the computational speed. In addition, rover body-fixed SLAM could improve the navigation accuracy of a rover and decrease the cumulative linearization error by coordinates transformation during the update process, which is shown in the simulation results.

The presence of code Doppler and navigation bit sign transitions means that the acquisition of global positioning system (GPS) signals is difficult in weak signal environments where the output signal-to-noise ratio (SNR) is significantly reduced. Post-correlation techniques are typically utilised to solve these problems. Despite the advantages of these techniques, the post-correlation techniques suffer from problems caused by the code Doppler and the navigation bit sign transitions. We present an improved semi-bit differential acquisition method which can improve the code Doppler and the bit sign transition issues in the post-correlation techniques. In order to overcome the phenomenon of navigation bit sign transitions, the proposed method utilises the properties of the navigation bit. Since each navigation bit takes as long as 20 ms, there would be 10 ms correlations duration integration time between the received signal and the local coarse/acquisition (C/A) code in which the navigation bit sign transitions will not occur. Consequently, this problem can be cancelled by performing 10 ms correlations in even and odd units separately. Compensation of the code Doppler is also accomplished by shifting the code phase of the correlation results. To validate the performance of our suggested method, simulations are performed based on three data sets. The results show that the quantity of required input SNR to detect at least four satellites in the proposed method is − 48·3 dB, compared with − 20 dB and − 9 dB, respectively, in traditional differential and non-coherent methods.

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.

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 common view time transfer and two-way time and frequency transfer methods are currently the main means for achieving time synchronisation at nanosecond level. However, these methods have some limitations in real time and cost, which limit their wide applications in many fields, such as time synchronisation among base stations of the upcoming 5G network. In order to meet the requirements of nanosecond time synchronisation, a low-cost differential timing method is proposed in this paper by changing the manner of generation of traceability model parameters in GNSS navigation messages. The time deviation between GNSS system time and the timing laboratory that maintains Coordinated Universal Time (UTC) kept by timing laboratory named k (UTC(k)) is monitored by receiving the GNSS signal in space with monitoring receivers. The new traceability model parameters are generated with the monitored time deviations and then broadcast to users through the GNSS navigation message. The precision of the one-way timing method can be improved from tens of nanoseconds to the order of several nanoseconds with the proposed method. In addition, there are obvious advantages to carry out this method on the geostationary satellites in the BeiDou navigation satellite (BDS) constellation. The proposed method is verified on an experimental platform based on the UTC(NTSC) time frequency signal and the geostationary satellites in the BDS-3 constellation.

To reduce the operational complexity of the multipath estimating delay lock loop (MEDLL) and improve its anti-multipath performance for strobe correlators, a combination anti-multipath scheme, namely, the MEDLL on-strobe correlation technique, is proposed for global navigation satellite system (GNSS) signal processing. Short-delay multipath rays are separated from the strobe correlation function by the MEDLL mechanism; the dot product between the estimation residue and the standard correlation function or the BOC-PRN correlation function is then computed to eliminate the potential tracking ambiguity. Finally, this non-coherent combination result is sent to the loop filter to obtain anti-multipath code tracking. The proposed method is analysed via simulator data with a software receiver under different front-end bandwidth conditions. The results corroborate the better multipath mitigation capability and lower computational burden, although it is still difficult to eliminate all multipath interference, especially when the front-end bandwidth is insufficient.

This work quantitatively analyses vessel traffic service (VTS) communications in ports and suggests improvements for more efficient control of the service. For this purpose, analysis of VTS communications was performed on VHF channel 12 in Busan North Port, South Korea. This communications service follows the queue of M/G/1 (the arrivals have a Poisson distribution, the service time is characterized by a general distribution, and with a single server). The degree of congestion of the communication channel was shown as the utilisation rate of the queue, which was 67·7% at peak times and 29·6% at non-peak times. To reduce congestion in the communication channel, we propose to separate the peak time control channel, exclude passing reporting, and decrease the reporting time. With separation of the peak time control channel, the utilisation rate decreased by 41·1%. The utilisation rate decreased by 5·7% when passing reporting was omitted, and by 8·3% when reporting time was reduced by 60%. The results of this study can be used as basic policy data to improve VTS, including reinforcement of the VTS officer's role and adjustment of the control report contents.

Navigation methods, traditional and modern, use lines of position in the plane. Standard Gaussian assumptions about errors leads to a constant sum of squared distances from the lines defining a probability contour. It is well known these contours are a family of ellipses centred on the most probable position and they can be computed using algebraic methods. In this paper we show how the most probable position, the axes and foci of ellipses can be found using geometric methods. This results in a ruler and compasses construction of these points and this gives insight into the way the shape and orientation of the probability contours depend on the angles between the lines of position. We start with the classical case of three lines of position with equal variances, we show how this can be extended to the case where the variances in the errors in the lines of position differ, and we go on to consider the case of four lines of position using a methodology that generalises to an arbitrary number of lines.

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.

People with physical disabilities often face many challenges due to the non-compliance of public buildings to accessibility standards. Hence, it is necessary to provide them with relevant information about the quality of access associated with the environment they plan to visit. In this paper, we propose ‘AccessVOR’ (Accessibility assessment based on VORonoï Diagram), a novel approach that aims to automatically generate an indoor navigation network and to assess its accessibility for people moving with wheelchairs based on the American with Disabilities Act Accessibility Guidelines (ADAAG). A semantically enriched spatial database is developed based on ADAAG and the Indoor Geography Markup Language (IndoorGML) standard. A Three-Dimensional (3D) navigation-graph is then generated from the various components of an indoor environment using a Voronoï Diagram. The semantics of ADAAG allow assessing the accessibility of each segment of this navigation graph. Next, a navigation cost is allocated to this graph based on the accessibility of each segment of the network graph for navigation purposes.