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.

Maritime anomaly detection can improve the situational awareness of vessel traffic supervisors and reduce maritime accidents. In order to better detect anomalous behaviour of a vessel in real time, a method that consists of a Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and a recurrent neural network is presented. In the method presented, the parameters of the DBSCAN algorithm were determined through statistical analysis, and the results of clustering were taken as the traffic patterns to train a recurrent neural network composed of Long Short-Term Memory (LSTM) units. The neural network was applied as a vessel trajectory predictor to conduct real-time maritime anomaly detection. Based on data from the Chinese Zhoushan Islands, experiments verified the applicability of the proposed method. The results show that the proposed method can detect anomalous behaviours of a vessel regarding speed, course and route quickly.

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.

Two pre-processes for Automatic Identification System (AIS) trajectories commonly reported in the maritime knowledge discovery literature are trajectory simplification and event identification. Both pre-processes reduce storage and computational expenses by reducing the number of data points to be used in an analysis. This paper presents an event identification and trajectory simplification method based on behaviour identification and translation. Trajectory segments deemed to correspond to coastal or ocean navigation are translated into equivalent passage plan segments; a succinct description of the movements and behaviour of the ship. As a trajectory simplification method, it provides two main advantages over commonly used trajectory simplification methods: more meaningful simplified trajectories with better encoding of basic behaviours and the possibility to retain interesting behaviours in full resolution. As an event identification method, it is capable of differentiating between normal ocean or coastal navigating behaviour and complex or interesting behaviour, such as pilotage, reaction to a traffic conflict, or an involuntary deviation from the passage plan.

The trajectory tracking of Autonomous Underwater Vehicles (AUV) is an important research topic. However, in the traditional research into AUV trajectory tracking control, the AUV often follows human-set trajectories without obstacles, and trajectory planning and tracking are separated. Focusing on this separation, a trajectory re-planning controller based on Model Predictive Control (MPC) is designed and added into the trajectory tracking controller to form a new control system. Firstly, an obstacle avoidance function is set up for the design of an MPC trajectory re-planning controller, so that the re-planned trajectory produced by the re-planning controller can avoid obstacles. Then, the tracking controller in the MPC receives the re-planned trajectory and obtains the optimal tracking control law after calculating the object function with a Sequential Quadratic Programming (SQP) optimisation algorithm. Lastly, in a backstepping algorithm, the speed jump can be sharp while the MPC tracking controller can solve the speed jump problem. Simulation results of different obstacles and trajectories demonstrate the efficiency of the proposed MPC trajectory re-planning tracking control algorithm for AUVs.

Differential Global Positioning Systems (DGPS) and the European Geostationary Navigation Overlay Service (EGNOS) are included in a group of supporting systems (Ground-Based Augmentation System (GBAS)/Space-Based Augmentation System (SBAS)) for the American GPS. Their main task is to ensure better positioning characteristics (accuracy, reliability, continuity and availability) compared to GPS. Therefore, they are widely applied wherever GPS failures affect human safety, mainly in aviation, land and marine navigation. The aim of this paper is to assess the predictable positioning accuracy of DGPS and EGNOS receivers using a vessel manoeuvring in the Bay of Gdansk. Two receivers were used in the study: a Simrad MXB5 (DGPS) and a Trimble GA530 (EGNOS), which were simultaneously recording their coordinates. The obtained values were compared with the trajectory computed using a geodetic Global Navigation Satellite System (GNSS) receiver (Trimble R10) connected to a GNSS network, ensuring an accuracy of 2–3 cm (p = 0·95). During a four-hour measurement session, the accuracy statistics of these systems were determined based on around 11,500 positionings. Studies have shown that both positioning systems ensure a similar level of accuracy of their positioning services (approximately 0·5–2 m) and they meet the accuracy requirements set in published standards.

Airborne-Pseudolite (A-PL) systems have been proposed to augment Global Navigation Satellite Systems (GNSSs) in difficult areas where GNSS-only navigation cannot be guaranteed due to signal blockages, signal jamming, etc. One of the challenges in realising such a system is to determine the coordinates of the A-PLs to a high accuracy. The GNSS Precise Point Positioning (PPP) technique is a possible alternative to differential GNSS techniques such as those that generate Real-Time Kinematic (RTK) solutions. To enhance the A-PL positioning performance in GNSS challenged areas, it is assumed that inter-PL range measurements are also used in addition to GNSS measurements. When processing these new measurements, cross-correlations among A-PL estimated states introduced during measurement updates need to be accounted for so as to obtain consistent estimated states. In this paper, a distributed algorithm based on a Split Covariance Intersection Filter (SCIF) is proposed. Three commonly used means of implementing the SCIF algorithm are analysed. Another challenge is that real-time GNSS PPP relies on the use of precise satellite orbit and clock information. One problem is that these real-time orbit and satellite clock error corrections may not be always available, especially for moving A-PLs in challenging environments when signal outages occur. To maintain A-PL positioning accuracy using GNSS PPP, it is necessary to predict these error corrections during outages. Different prediction models for orbit and clock error corrections are discussed. A test was conducted to evaluate the A-PL positioning based on GNSS PPP and inter-PL ranges, as well as the performance of error prediction modelling. It was found that GNSS PPP combined with inter-PL ranges could achieve better converged positioning accuracy and a reduction in convergence time of GNSS PPP. However, the performance of GNSS PPP with inter-PL ranges was degraded by observing A-PLs with limited positioning accuracy. Although the performance improvement achieved by the SCIF-based distributed algorithms was smaller than that by the centralised algorithm, greater robustness in dealing with deteriorated observed A-PLs' trajectory data was demonstrated by the distributed algorithms. In addition, short-term prediction models were analysed, and their performance was shown to reduce the effect of error correction outages on A-PL positioning accuracy.

Modern ship simulators enable simulations of reality using available environment and ship models. When choosing a specific vessel from a catalogue, however, it is not always immediately apparent as to how true a simulation is to the original vessel. Its makers are required only to have software certificates, which does not ensure the exact modelling of a ship in the simulation. This paper presents research in continuation of previous work presenting a general methodology for the evaluation of the degree of accuracy of a simulated ship model compared to its real-world counterpart. In this paper, the results are shown of a comparative analysis based on actual measurements with the use of one of the methods of multi-criteria analysis. Furthermore, the methodology for the construction of ship models is presented. The paper concludes with a test verifying the accuracy of the assumptions.

The tourist attraction of a cruise itinerary is composed of the on board experience plus the shore-based experience. Due to the positive dynamism of the cruise industry since the beginning of the twenty-first century, cruise lines are driven to innovate to create new experiences that help maintain high demand rates. From the point of view of creating new experiences on land, cruise lines move their vessels from one destination region to another to maximise the vessel's occupancy and to offer itineraries with a wider variety of shore-based attractions. These new itinerary designs lead to alterations in the seasonality patterns of the neighbouring regions. In this work, the 17 most important cruise ports located in the northeast quadrant of the Atlantic Ocean are analysed to find groups of ports with homogeneous seasonality patterns using clustering techniques. The analysis showed two different seasonality patterns. Consequently, some implications to improve the use of the ports of both clusters are included.

Connected and Autonomous Vehicles (CAVs) have been researched extensively for solving traffic issues and for realising the concept of an intelligent transport system. A well-developed positioning system is critical for CAVs to achieve these aims. The system should provide high accuracy, mobility, continuity, flexibility and scalability. However, high-performance equipment is too expensive for the commercial use of CAVs; therefore, the use of a low-cost Global Navigation Satellite System (GNSS) receiver to achieve real-time, high-accuracy and ubiquitous positioning performance will be a future trend. This research used RTKLIB software to develop a low-cost GNSS receiver positioning system and assessed the developed positioning system according to the requirements of CAV applications. Kinematic tests were conducted to evaluate the positioning performance of the low-cost receiver in a CAV driving environment based on the accuracy requirements of CAVs. The results showed that the low-cost receiver satisfied the “Where in Lane” accuracy level (0·5 m) and achieved a similar positioning performance in rural, interurban, urban and motorway areas.

The Navigation with Indian Constellation (NavIC)/Indian Regional Navigation Satellite System (IRNSS) is an emerging satellite navigation system that provides an independent navigation system for positioning and timing services in India and up to 1,500 km from its borderline. The dual frequency NavIC system uses the L5 frequency and S-band for navigation. These navigation signals are extremely weak and susceptible to interference when they are received on Earth's surface. Moreover, the performance of these bands may be degraded by other band or out-of-band communication systems, which can become the major threat to the performance of a NavIC receiver. The main focus of this paper is to detect real-time interference of Wi-Fi signals in the S-band of the NavIC receiver. The results are prepared with respect to the Power Spectral Density (PSD), execution of acquisition stage and the detection of Wi-Fi interference with two sample hypothesis testing methods including the Kolmogorov-Smirnov (KS)-test, the t-test and the Variance (var)-test. A performance analysis of the p-value is used to measure the evidence of interference existence for hypothesis testing, decision hypothesis and probability of detection are evaluated for each hypothesis method. The results show the severity of the Wi-Fi signal as a potential source of interference for future NavIC applications.

This paper presents a real-time and deterministic path planning method for autonomous ships or Unmanned Surface Vehicles (USV) in complex and dynamic navigation environments. A modified Artificial Potential Field (APF), which contains a new modified repulsion potential field function and the corresponding virtual forces, is developed to address the issue of Collision Avoidance (CA) with dynamic targets and static obstacles, including emergency situations. Appropriate functional and safety requirements are added in the corresponding virtual forces to ensure International Regulations for Preventing Collisions at Sea (COLREGS)-constrained behaviour for the own ship's CA actions. Simulations show that the method is fast, effective and deterministic for path planning in complex situations with multiple moving target ships and stationary obstacles and can account for the unpredictable strategies of other ships. The authors believe that automatic navigation systems operated without human interaction could benefit from the development of path planning algorithms.

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.

Precise Point Positioning/Inertial Navigation System (PPP/INS) integrated navigation based on PPP and low-accuracy INS is often used to provide position and attitude information for vehicle-mounted or airborne mobile mapping systems. With proper processing, the position accuracy of PPP/INS is comparable to that of Differential Global Navigation Satellite System (DGNSS)/INS, but the accuracy of the attitude, especially the yaw angle, cannot be guaranteed. However, the yaw angle is crucial for mobile mapping systems. To compensate for the insufficiency of PPP/INS, we have designed a Multi-Antenna GNSS (MAGNSS)/INS integrated navigation system. First, the attitude determination method using MAGNSS is presented in detail. Then, the MAGNSS attitude is combined with the PPP position and velocity as measurements for integration with the INS. Thus, PPP/INS integrated navigation was improved to MAGNSS/INS integrated navigation. Finally, a three-hour car-borne test was conducted to evaluate the performance of the proposed method. The results indicate that the attitude determined from MAGNSS is accurate and stable over time. Compared to PPP/INS, MAGNSS/INS integrated navigation can improve the attitude accuracy significantly because of the inclusion of MAGNSS attitude.

Radiolocation systems for aviation based on Multi-Lateration (MLAT) typically use a set of synchronised ground sensors to receive radio signals broadcast by onboard transmitters. In most cases, the sensor synchronisation in Wide Area Multi-Lateration Systems (WAM) is provided by Global Navigation Satellite System (GNSS) receivers. However, in the case of synchronisation failure, there is still a possibility to estimate the coordinates of the tracked aircraft by using the measurements of the time of arrival taken by non-synchronised sensors. The article presents the principle of operation and equations for calculating the coordinates of an aircraft in an asynchronous multi-lateration system, together with the results of a computer simulation allowing comparison of the accuracy of position estimation between the asynchronous and the typical, synchronous MLAT. This paper contains also some comments on the required stability of the clock source for the sensors working in an asynchronous MLAT system.

A probabilistic methodology for separation loss probability assessments is proposed in this paper. The key focus is on the effect of uncertainties from multiple Automatic Dependent Surveillance-Broadcast (ADS-B) systems on the separation loss probability assessment. First, a brief review of the ADS-B system and its associated uncertainty quantification metrics is discussed. It is found that most existing studies focus on the individual ADS-B uncertainty quantification for a single aircraft, which is not sufficient for separation loss probability assessment when two or more aircraft are involved. Next, a probabilistic positioning model with multiple aircraft is proposed and various types of uncertainties are included in the proposed model. Numerical simulations show that a navigation satellite fault can significantly affect separation error when individual aircraft see different satellite sets. Following this, several demonstration examples are illustrated to show the bounds for separation loss probability estimation. Finally, several conclusions and suggestions are discussed based on this study. One major finding is that the separation risk significantly increases when two nearby aircraft use different satellite sets to navigate. Real-time assessment of this risk should be performed.

We investigate a strategy to address the problem of low aircraft detection probability of space-based Automatic Dependent Surveillance-Broadcast (ADS-B). A nineteen-element hexagonal array and adaptive multi-beamforming method is proposed. This method aims to adjust the beam pattern dynamically to reduce signal collision and enlarge coverage. With the focus on the mission requirement of global aircraft detection by 2020, the appropriate gain and direction of beams are studied and designed in detail. Theoretical analysis and simulations show that this adaptive multi-beam antenna can greatly improve flight detection probability at an average reporting interval from 10 seconds to 5 seconds when compared with the traditional fixed multi-beam antenna. The results of this work show that the design of a 19-element antenna along with the adaptive multi-beamforming method can be considered as a building block of future space-based ADS-B.

The accuracy and fault tolerance of filters are directly affected by the filter architecture and algorithm, thus influencing navigation performance. The chi square detection used in the conventional reset federated filter is not sensitive to soft faults, and it is easy to cause the health subsystem to be polluted through information sharing. It is a challenge to design an adaptive reset federated filter to improve the performance of the navigation system. Therefore, taking the Strapdown Inertial Navigation System/Global Positioning System/Celestial Navigation System/Synthetic Aperture Radar (SINS/GPS/CNS/SAR) integrated navigation system as an example, an adaptive federated filter architecture for vector-formed information sharing without a fault isolation module is designed in this paper. The proposed method uses the two-state chi square detection algorithm to calculate the parameters corresponding to each state, making the state with higher accuracy obtain a greater information distribution coefficient. In addition, according to the value of vector-formed information sharing, an adaptive coefficient of measurement noise is designed. This improves the adaptability of the navigation system to soft faults. Simulation results show that the accuracy of the proposed algorithm has the same performance compared with the conventional method under normal circumstances. When the sensor has a soft fault, the adaptive federated filter algorithm proposed in this paper can adaptively adjust the distribution coefficients, eliminate the influence of the fault information and improve the precision of the navigation system. The approach described in this paper can be used in multi-sensor integrated navigation. It will have better performance in engineering applications.

In order to investigate the benefits of compound waterways more fully, this study reveals vessel navigational mode and traffic conflicts in a compound waterway through a case analysis, following which a type of simplified prototype of a compound waterway is proposed and three key conflict areas are specified. Based on the three key sub-models of slot allocation for vessels in a waterway entrance, traffic flow conversion of a main and auxiliary waterway in a precautionary area, and traffic flow coordination of division and confluence in a Y crossing area, a vessel traffic scheduling optimisation model is presented, with the minimum waterway occupancy time and minimum total waiting time of vessels as the objective. Furthermore, a multi-objective genetic algorithm is proposed to solve the model and a simulation experiment is carried out. By analysing the optimised solution and comparing it with other scheduling schemes in common use, the results indicate that this method can effectively improve navigation safety and efficiency in a compound waterway.

In this paper, a novel algorithm of weighted k-means clustering with geodesic criteria is presented to generate a uniform database for a star sensor. For this purpose, selecting the appropriate star catalogue and desirable minimum magnitude and eliminating double stars are among the steps of the uniformity process. Further, Delaunay triangulation and determining the scattered data density by using a Voronoi diagram were used to solve the problems of the proposed clustering method. Thus, by running a Monte Carlo simulation to count the number of stars observed in different fields of view, it was found that the uniformity leads to a significant reduction of the probability of observing a large number of stars in all fields of view. In contrast, the uniformity slightly increased the field of view needed to observe the minimum number of required stars for an identification algorithm.