Superimposing Electronic Navigational Chart (ENC) data on marine radar images can enrich information for navigation. However, direct image superposition is affected by the performance of various instruments such as Global Navigation Satellite Systems (GNSS) and compasses and may undermine the effectiveness of the resulting information. We propose a data fusion algorithm based on deep learning to extract robust features from radar images. By deep learning in this context we mean employing a class of machine learning algorithms, including artificial neural networks, that use multiple layers to progressively extract higher level features from raw input. We first exploit the ability of deep learning to perform target detection for the identification of marine radar targets. Then, image processing is performed on the identified targets to determine reference points for consistent data fusion of ENC and marine radar information. Finally, a more intelligent fusion algorithm is built to merge the marine radar and electronic chart data according to the determined reference points. The proposed fusion is verified through simulations using ENC data and marine radar images from real ships in narrow waters over a continuous period. The results suggest a suitable performance for edge matching of the shoreline and real-time applicability. The fused image can provide comprehensive information to support navigation, thus enhancing important aspects such as safety.

This paper introduces an approach for solving a safe ship trajectory planning problem. The algorithm, utilising the concept of a discrete artificial potential field and a path optimisation algorithm, calculates an optimised collision-free trajectory for a ship. The method was validated by simulation tests with the use of real navigational data registered on board the research and training ship Horyzont II. Results of simulation studies demonstrate that the approach is capable of finding a collision-free trajectory in near-real time, and this proves its applicability in commercial collision avoidance systems for ships. The paper contributes to the development of decision support systems for ships and autonomous navigation.

The third generation of the BeiDou navigation satellite system (BDS-3) is a global navigation system, and is expected to be in full operation by 2020. High-precision orbits are a precondition for BDS-3 to provide a highly accurate service, which needs a global tracking and monitoring capability for the operational satellites. However, it is difficult for BDS to construct global ground monitoring stations. Fortunately, Ka-band Inter-Satellite Link (ISL) antennae fitted to the BDS-3 satellites can be used to extend the visible arc of the Medium Earth Orbit (MEO) satellites and to enhance the ground stations for orbit determination. This paper analyses the ISL-enhanced orbit determination for eight BDS-3 satellites, using the data from ten Chinese domestic stations and 13 international Global Navigation Satellite System (GNSS) Monitoring and Assessment System (iGMAS) overseas stations. The results show that the Three-Dimensional (3D) position Root Mean Square (RMS) error of the Overlapping Orbit Differences (OODs) is approximately 1 m when only ten regional stations are used. When the ISL measurements are added, the 3D position RMS error is decreased to 0·5 m, and the accuracy of the 24-hour orbit prediction can also be improved from 2 m to 0·7 m, which is even better than that of the orbits determined using globally distributed stations. It can be expected that with the subsequent launch of BDS-3 satellites and the increasing number of ISLs, the advantage of the ISL enhanced orbit determination will become more significant.

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.

To evaluate the aptness of a navigation system in a particular application, the designer needs to assess its performance over typical trajectories travelled by the vehicle itself. Moreover, he or she may be required to judge which components of the kinematics state may be better estimated (and which will not). The main contributions of this work are two novel and complementary performance measures that, in concert, allow for the assessment of a navigation system within the actual context of its application over specific trajectories. For a given on board instrumental configuration, the “excitability metric” permits the isolation of the contribution of the information conveyed by the vehicle's motion itself, while, the “sensability metric” measures the resultant overall quality of the kinematics state estimation. The same tools could help the designer planning appropriate vehicles manoeuvres in order to obtain a required precision for each estimated component. While emphasis is given on the mathematical justification of those metrics, their use is also illustrated with real flight data recorded from a sounding rocket.

The accuracy of speed prediction error to the next waypoint is a key factor in maintaining longitudinal separation on oceanic routes. This estimation is often used by air traffic control to estimate the future position of aircraft, and the estimation errors result in potential separation infringement. While most aircraft can calculate the estimated time at each future waypoint using the onboard Flight Management System, the factors affecting the inaccuracy of the estimation require more clarification. This paper investigates the accuracy of the speed prediction error on oceanic routes and examines the main factor of error using airline flight data. The results show that wind prediction error is a main source of speed prediction error, and significant differences of the speed prediction error among airlines and aircraft types were observed.

The integration of magnetometers and Inertial Navigation Systems (INS) is widely used in low-cost navigation systems. However, even if the system has been calibrated, random magnetic disturbances still appear in practical applications, which lead to large heading errors. To solve this problem, an adaptive anti-disturbance method to overcome random magnetic disturbance is proposed. First, disturbances are classified and analysed in detail based on actual road vehicle driving data. Then an Adaptive Robust Extend Kalman Filter (AREKF) is designed to resist sudden disturbances. However, an AREKF may accumulate errors slowly when a long-term disturbance exists. Considering this situation, this paper proposes that AREKF is used to maintain accuracy in the early stages, at the same time as the magnetometer is quickly calibrated with a Kalman filter. Then, the new magnetometer parameters are put into the AREKF to suppress long-term disturbances. Finally, cascading these two modules, not only the sudden disturbance can be overcome, but the situation of long-term disturbances can be suppressed. The results of simulation and an actual driving test show that the proposed method can effectively overcome random magnetic disturbances in both the short and long term.

Current Motion Compensation (MOCO) methods using Inertial Navigation System (INS)/Global Positioning System (GPS) integrated systems have provided an important advance in Synthetic Aperture Radar (SAR) imagery, but most of these methods only work well over a short imaging period. With the development of high-resolution SAR that provides image gathering over long periods, the need for higher levels of INS/GPS performance than normally available is desired. The higher requirement of INS/GPS for SAR MOCO is two-fold: (1) the accurate knowledge of location information, and (2) the smoothness of relative change in navigation error. In this paper, we design an INS/GPS architecture with dual-filter correction to obtain accurate absolute velocity and position measurement information with smooth low relative error noise over a long image gathering period. Real SAR data experimental results show that the proposed method effectively improves the MOCO performance of INS/GPS with long SAR imaging periods, in which the SAR azimuth resolution reaches 1·45 m, which is very close to the design value of 1 m.

The absence of a regional, open water vessel collision risk assessment system endangers maritime traffic and hampers safety management. Most recent studies have analysed the risk of collision for a pair of vessels and propose micro-level risk models. This study proposes a new method that combines density complexity and a multi-vessel collision risk operator for assessing regional vessel collision risk. This regional model considers spatial and temporal features of vessel trajectory in an open water area and assesses multi-vessel near-miss collision risk through danger probabilities and possible consequences of collision risks via four types of possible relative striking positions. Finally, the clustering method of multi-vessel encountering risk, based on the proposed model, is used to identify high-risk collision areas, which allow reliable and accurate analysis to aid implementation of safety measures.

Bathymetric Electronic Navigational Charts (bENCs) contain only bathymetry data and can be used in applications such as underwater positioning, dredging and piloting. According to International Hydrographic Organization (IHO) standard S-57, Electronic Navigational Charts (ENCs) contain depth information with pure density of depth contours. Typical depth contours encoded by Hydrographic Offices are limited to 2, 5, 10 and 20 m. Availability of more depth contours in bENCs would allow the visualisation of a safety contour which is closer to users' specific needs, especially in restricted waters such as ports, lakes and rivers. Another problem is non – Global Navigation Satellite System (GNSS) Unmanned Underwater Vehicle (UUV) navigation. bENCs could be used as reference data for UUV comparative navigation. This is called terrain reference navigation. This article presents the results from bathymetric data processing that was performed to convert data contained in bENCs into a reference for underwater comparative navigation. We use data obtained using a multibeam echo sounder to produce depth data with a horizontal spacing of 0·10 m that is suitable for use in restricted waters. The experimental data was collected in and around the Port of Gdansk, Poland.

The quality of Automatic Identification System (AIS) data is of fundamental importance for maritime situational awareness and navigation risk assessment. To improve operational efficiency, a deep learning method based on Bi-directional Long Short-Term Memory Recurrent Neural Networks (BLSTM-RNNs) is proposed and applied in AIS trajectory data restoration. Case studies have been conducted in two distinct reaches of the Yangtze River and the capability of the proposed method has been evaluated. Comparisons have been made between the BLSTM-RNNs-based method and the linear method and classic Artificial Neural Networks. Satisfactory results have been obtained by all methods in straight waterways while the BLSTM-RNNs-based method is superior in meandering waterways. Owing to the bi-directional prediction nature of the proposed method, ship trajectory restoration is favourable for complicated geometry and multiple missing points cases. The residual error of the proposed model is computed through Euclidean distance which decreases to an order of 10 m. It is considered that the present study could provide an alternative method for improving AIS data quality, thus ensuring its completeness and reliability.

In Air Traffic Control (ATC), aircraft altitude data is used to keep an aircraft within a specified minimum distance vertically from other aircraft, terrain and obstacles to reduce the risk of collision. Two types of altitude data are downlinked by radar; actual flight level (Mode C) and selected altitude (Mode S). Flight level indicates pressure altitude, also known as barometric altitude used by controllers for aircraft vertical separation. ‘Selected altitude’ presents intent only, and hence cannot be used for separation purposes. The emergence of Global Navigation Satellite Systems (GNSSs) has enabled geometric altitude on board and to the controllers via the Automatic Dependent Surveillance-Broadcast (ADS-B) system. In addition, ADS-B provides quality indicator parameters for both geometric and barometric altitudes. Availability of this information will enhance Air Traffic Management (ATM) safety. For example, incidents due to Altimetry System Error (ASE) may potentially be avoided with this information. This work investigates the use and availability of these parameters and studies the characteristics of geometric and barometric data and other data that complement the use of these altitude data in the ADS-B messages. Findings show that only 8·7% of the altitude deviation is < 245 feet (which is a requirement of the International Civil Aviation Organization (ICAO) to operate in Reduced Vertical Separation Minimum (RVSM) airspace). This work provides an alert/guidance for future ground or airborne applications that may utilise geometric/barometric altitude data from ADS-B, to include safety barriers that can be found or analysed from the ADS-B messages itself to ensure ATM safety.

An airport can be a stressful place for passengers. One of the reasons to get stressed might be the result of poor wayfinding. Current wayfinding signs are often static, which makes them difficult to adapt to new situations. In contrast, dynamic signs can be updated and adjusted accordingly. Light projections can be used as dynamic signs. The aim of this study is to understand if the use of animated projections onto the floor can improve the wayfinding experience. Four animations have been developed and tested within a controlled testing environment of which one animation has been tested in a real airport environment. Results indicate that animation for wayfinding purposes should show a clear vertical motion to guide towards a certain direction. Additionally, higher velocity in the animation was perceived as more positive. The observation in the airport showed that a projection in clear daylight and on the floor is not noticed by the passengers walking by.

Effective technical methods for verifying the authenticity and accuracy of Automatic Identification System (AIS) data, which are important for safe navigation and traffic regulation, are still lacking. In this study, we propose a new method to verify AIS data by using video images taken by an Unmanned Aerial Vehicle (UAV). An improved ViBe algorithm is used to extract the ship target image from the video images and the ship's spatial position is calculated using a monocular target-positioning algorithm. The positioning results are compared with the position, speed and course data of the same ship in AIS, and the authenticity and accuracy of the AIS data are verified. The results of the experiment conducted in the inland waterways of Huangpu River in Shanghai, China, show that AIS signals can be automatically checked and verified by a UAV in real time and can thus improve the supervision efficiency of maritime departments.

In order to determine fairway width accurately and to ensure an adequate level of safety, it is necessary to fulfil different safety standards and user needs. There are a number of international recommendations for fairway design, but the recommendations by Permanent International Association of Navigation Congresses (PIANC), Puerto Del Estado (ROM 3·1) and the Japanese Ministry of Land, Infrastructure, Transport and Tourism (MLIT) are some of the best known. However, in all of these recommendations, additional width due to ship-bank effect is obsolete and needs to be improved. The objective of this paper is to use a navigational simulator with a predefined ship-bank interaction model and fine form ships models to determine the ship trajectory caused by ship-bank effect. The methodology of research used in the paper consisted of using ship trajectory data to propose a deterministic model for improving fairway additional width due to ship-bank effect. Results showed that such a method is not time-consuming and can improve fairway design in terms of ship-bank effect, increasing additional width accuracy.

Global Navigation Satellite System (GNSS) observations contain various errors, the separation and measurement of which is a popular research topic. Multipath effect on code measurements is investigated through the multipath combination, but carrier multipath error is small, and it is difficult to distinguish from other errors, such as hardware delay, carrier noise and satellite inherent biases. However, as the number of frequency points increases during the rapid development of GNSSs, it is possible to analyse the abovementioned errors in detail. Triple-frequency combination can be used to eliminate the first order ionospheric error, and a quad-frequency combination has one degree of freedom, which may be used to minimise carrier error effects. For this reason, an optimum method has been developed for multi-frequency GNSS code-multipath combination measurements, which has been verified by exploiting BeiDou System (BDS), three frequency data from an International GNSS Service (IGS) station and a city canyon as well as actual sampled quad-frequency data. By comparative analysis, we found that the fluctuations of an optimum triple-frequency combination are smaller than that of the non-optimum combination, which decreases the influence of inherent errors and biases on carrier phase. At the same time, second-order ionospheric error can be effectively eliminated as well. This provides a new code-multipath combination measurement optimisation methodology for future multi-frequency BDS and other GNSSs.

Connected-Element Interferometry (CEI) is a technique for measuring the phase delay of difference of Time Of Arrival (TOA) of a downlink radio signal to two antennae on a short baseline. This technique can use an atomic clock for time-frequency transmission and achieve intermediate accuracy angular tracking. Owing to the relatively short length of the baseline, the passive reception mode, and near real-time operation, CEI can be used to continuously monitor the orbit variations of both cooperative and non-cooperative satellites. In this paper, a small-scale CEI system of two orthogonal baselines (75 m × 35 m) is investigated to track a Geostationary Earth Orbit (GEO) Television (TV) satellite at 110·5°E. The phases are extracted from correlation results. The results show that the Root Mean Square (RMS) of the phase fitting residuals, if not calibrated, is within 2° at night and up to 10° in the daytime. After applying the calibration signal, the RMS of the phase fitting residuals in the daytime decreases to the same level at night. Comparing the phase delay with the a priori phase delay using Two-Line-Element (TLE) data, the integer ambiguity is successfully resolved. Finally, a batch algorithm is used to estimate the orbit of the GEO satellite, and the orbit determination accuracy is evaluated using the precise orbits provided by the China National Time Service Centre (NTSC). The results show that the accuracies in the radial direction and the cross-track direction are less than 1 km, and the Three-Dimensional (3D) position accuracy reaches the 2 km order of magnitude.

BeiDou signals are modulated with a Neumann-Hofman (NH) code of 1 kbps. The frequent bit transitions lead to a sensitivity attenuation of classic acquisition algorithms. In order to increase acquisition sensitivity for weak BeiDou signals, a novel algorithm based on modified zero-padding and differential correlation is proposed. First, a zero-padding method is used to weaken the effect of NH code. Second, the differential coherent delay time is modified to 20 ms to remove the influence of data bit transitions. The integration time is extended to 10 ms to increase acquisition sensitivity. Finally, Monte Carlo simulations and real data tests are conducted to analyse the performance of the proposed algorithm. Simulated results show that the proposed acquisition algorithm outperforms traditional algorithms under a Carrier-to-Noise ratio (C/N0s) of 20~38 dB-Hz. The sensitivity of the proposed algorithm is about 10dB higher than traditional 6 ms repeated search algorithms. Real data test results show that the proposed algorithm outperforms the traditional method with weak signals. This algorithm can remove the effect of NH code and effectively increase the acquisition sensitivity. The proposed algorithm is suitable for acquisition of weak BeiDou signals.