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.

SESAR is Europe's ‘Single European Sky Air traffic Research system’. NextGen is the USA's ‘Next Generation Air Transport System’. SESAR and NextGen are developments targeted at post 2020. The common vision is to integrate and implement new technologies to improve air traffic management (ATM) performance – a ‘new paradigm’. SESAR and NextGen combine increased automation with new procedures to achieve safety, economic, capacity, environmental, and security benefits. The systems do not have to be identical, but must have aligned requirements for equipment standards and technical interoperability.

A key component is a ‘cooperative surveillance’ model, where aircraft are constantly transmitting their position (from navigational satellites), flight path intent, and other useful aircraft parameters – known as ADS-B (Automatic Dependent Surveillance-Broadcast). The focus for planning and executing system operations will increasingly be aircraft 4D trajectories: a 4D trajectory is the aircraft path, three space dimensions plus time, from gate-to-gate, i.e. including the path along the ground at the airport.

In analysing potential major ATM system changes, a simple division into five Key Test areas might be: Safety Credibility, Operational Concept, Technological Feasibility, Benefits and Costs, and Transition Path. The main attention here is on Benefits and Costs of SESAR. The strategic challenge will be to convince customers and stakeholders of the benefits of paradigm shift expenditure, given the associated impacts on future user charges, aircraft equipment investments and public expenditure. The analysis here shows that the existing cost benefit analysis results for SESAR are not particularly robust, possibly over-estimating Net Present Values by some tens of € billions.

Collision avoidance is an intensive discussion issue for navigation safety. This article introduces a new routing algorithm for finding optimal routes with collision detection and avoidance on raster charts or planes. After the required data structure of the raster chart is initialized, the maze routing algorithm is applied to obtain the particular route of each ship. Those ships that have potential to collide will be detected by simulating the particular routes with ship domains. The collision avoidance scheme can be achieved by using the collision-area-marking method with collision avoidance rules at sea. The algorithm has linear time and space complexities, and is sufficiently fast to perform real-time routing on the raster charts.

Maritime video surveillance has become an essential part of the vessel traffic services system, intended to guarantee vessel traffic safety and security in maritime applications. To make maritime surveillance more feasible and practicable, many intelligent vision-empowered technologies have been developed to automatically detect moving vessels from maritime visual sensing data (i.e., maritime surveillance videos). However, when visual data is collected in a low-visibility environment, the essential optical information is often hidden in the dark, potentially resulting in decreased accuracy of vessel detection. To guarantee reliable vessel detection under low-visibility conditions, the paper proposes a low-visibility enhancement network (termed LVENet) based on Retinex theory to enhance imaging quality in maritime video surveillance. LVENet is a lightweight deep neural network incorporating a depthwise separable convolution. The synthetically-degraded image generation and hybrid loss function are further presented to enhance the robustness and generalisation capacities of LVENet. Both full-reference and no-reference evaluation experiments demonstrate that LVENet could yield comparable or even better visual qualities than other state-of-the-art methods. In addition, it takes LVENet just 0⋅0045 s to restore degraded images with size 1920 × 1080 pixels on an NVIDIA 2080Ti GPU, which can adequately meet real-time requirements. Using LVENet, vessel detection performance can be greatly improved with enhanced visibility under low-light imaging conditions.

In the first part of this series of papers an outline was given of the approach made at the Royal Aircraft Establishment to the problems of estimating collision risk and of specifying the quality of navigation needed to make separation standards safe. It was stressed that estimates should be based on intensive observation of flying errors, rather than on speculative theories, and that it is more feasible to develop ‘upper limit’ estimating techniques than those which purport to give the exact risk. In summary, a list of seven ‘requirements’ was given, as a reminder of the essential principles which can so easily be overlooked in the piecemeal task of relating separation standards to collision risk.

The purpose of this paper is to show some of the theoretical techniques which have been developed at R.A.E. to satisfy five of these requirements. (The remaining two do not call for special techniques and will be dealt with when practical applications are described in Part III.) The paper contains three Appendixes, dealing with the frequency of losing separation in one dimension, the computation of P's from the assumed tail shapes, and the treatment of relative errors. These are not included here but will appear in the off-printed version which may be obtained from the Royal Aircraft Establishment.

Both this paper and the paper that follows by Mr. Attwooll are crown copyright and are reproduced with the permission of H.M. Stationery Office.

In this article formulas useful for the calculation of aircraft mid-air collision probabilities at intersecting air routes are developed. The aircraft overlap density, a key parameter in the calculation, is expressed as a function of the intersection angle of air routes, aircraft speeds, the nominal separation, and parameters in the position-error distribution. Two representative probability models for position errors are used to illustrate the computational procedures suggested. A method of approximation over large navigation systems is also proposed.

The calculation of aircraft mid-air collision probabilities is an important step in the design of air-route structure and is a key element in the specification of separation standards and minimum requirements of facilities reliability and accuracy. A thorough analysis of collision probabilities for long-range parallel air routes over oceanic areas was reported by P. G. Reich in three research documents and in a series of papers published in this Journal in 1966. Analysis of collision probabilities at intersecting air routes typical in off-shore and continental areas, however, has not been fully explored to date. The only direct reference available on this subject appears to be the work by Bellantoni,7 in which a collision problem was formulated in the three-dimensional space and was apt to deal with airport terminal landing or take-off situations. For circumstances where horizontal linear air routes intersect one another at preassigned positions, the analysis provided by Bellantoni needs to be simplified and refashioned for use in extensive applications.

A new navigation method, called a Line of Sight Counteraction Navigation (LOSCAN) algorithm has been introduced to aid manoeuvre decision making for collision avoidance based on a two-ship encounter. The LOSCAN algorithm is derived from an extension of the basic principle of traditional missile proportional navigation, recognising that the objective of the latter is target capture rather than target avoidance. The basic concept is to derive an acceleration command so as to increase the misalignment between the ships' relative velocity and the line-of-sight. The algorithm includes a risk assessment and the generation of appropriate navigation commands to manoeuvre own ship free of collision if a risk of collision exists. Numerical examples have been used to demonstrate the effectiveness of the algorithm. The relationship between the distance at the closest point of approach with respect to early warning distance, and with the norm of the acceleration, has also been analysed. In operation, the collision avoidance decision making process is a complicated problem, with its solution subject to ship states, practical dynamic constraints, Collision Avoidance Regulations (COLREGS), encountering ship manoeuvre coordination and human decision making factors. The proposed algorithm provides a consistent manoeuvre signal to aid decision-making.

Underwater terrain matching navigation technology is an important research area for the underwater navigation of Autonomous Underwater Vehicles (AUVs). Terrain matching navigation can realise long-term, subtle, all-weather, and high-precision underwater AUV navigation. In this paper, the research status of the application of AUV underwater terrain matching navigation is reviewed, the system composition, theory and terrain matching methods of underwater terrain matching navigation are summarised and the advantages of a multi-beam bathymetric system in underwater terrain matching navigation are discussed. The current research thoughts are summarised, the key issues are pointed out, and possible future development trends are discussed.

The Strait of Istanbul is one of the most congested and risky waterways in the world. Navigation patterns have been investigated using Automatic Indentification System (AIS) data collected over a long period. 1·5 billion AIS messages, gathered over a year from 309,000 moving vessels in the Strait were stored in a Structured Query Language (SQL) database. Grid-based analysis is used to track the time, number, position, type, dimension, heading, speed and course over ground of ships. Local traffic, whose effect on maritime risk has often been neglected, is found to dominate transit traffic by a ratio of eight to one. Vessel distributions indicate that the most common lengths of vessels are 100 m and 170 m. Draught analysis shows a net transfer of goods from north to south. Southbound vessels are more likely to exceed the enforced speed limit due to predominant currents. Courses indicate that the local traffic strongly affects navigation patterns, especially at sectors with sharp turns. All these results help to understand the navigation patterns of ships and give the necessary input to assist in predicting maritime risk.

In the integrated navigation system using extended Kalman filter (EKF), the state error conventionally uses linear approximation to tackle the commonly nonlinear problem. However, this error definition can diverge the filter in some adverse situations due to significant distortion of the linear approximation. By contrast, the nonlinear state error defined in the Lie group satisfies the autonomous equation, which thus has distinctively better convergence property. This work proposes a novel strapdown inertial navigation system (SINS) nonlinear state error defined in the Lie group and derives the SINS equations of the Lie group EKF (LG-EKF) for the MIMU/GNSS/magnetometer integrated navigation system. The corresponding measurement equations are also derived. A land vehicle field test has been conducted to evaluate the performance of EKF, ST-EKF (state transformation extended Kalman filter) and LG-EKF, which verifies LG-EKF's superior estimation accuracy of the heading angle as well as the other two horizontal angles (pitch and roll). The LG-EKF proposed in this paper is unlimited in the choice of sensors, which means it can be applied with both high-end and low-end inertial sensors.

A loosely coupled Inertial Navigation System (INS) and Global Positioning System (GPS) are studied, particularly considering the constant lever arm effect. A five-element vector, comprising a craft's horizontal velocities in the navigation frame and its position in the earth-centred and earth-fixed frame, is observed by GPS, and in the presence of lever arm effect, the nonlinear observation equation from the state vector to the observation vector is established and addressed by the correction stage of an unscented Kalman filter (UKF). The conditionally linear substructure in the nonlinear observation equation is exploited, and a computationally efficient refinement of the UKF called marginalized UKF (MUKF) is investigated to incorporate this substructure where fewer sigma points are needed, and the computational expense is cut down while the high accuracy and good applicability of the UKF are retained. A performance comparison between UKF and MUKF demonstrates that the MUKF can achieve, if not better, at least a comparable performance to the UKF, but at a lower computational expense.

To ensure high accuracy results from an integrated GPS/INS system, the carrier phase observables have to be used to update the filter's states. As a prerequisite the integer ambiguities must be resolved before using carrier phase measurements. However, a cycle slip that remains undetected (and uncorrected) will significantly degrade the filter's performance. In this paper, an algorithm that can effectively detect and identify any type of cycle slip is presented. The algorithm uses additional information provided by the INS, and applies a statistical technique known as the cumulative-sum (CUSUM) test. In this approach, cycle slip decision values can be computed from the INS-predicted position (due to the fact that its short-term accuracy is very high), and the CUSUM test used to detect cycle slips (as it is very sensitive to abrupt changes of mean values). Test results are presented to demonstrate the effectiveness of the proposed algorithm.

When ships approach each other, they should keep a minimum area around them clear of other vessels in order to remain safe. The geometrical shape of this area has been studied since the early 1970s and is defined as the ship domain. The progress in computer capacity since then and the introduction of the Automatic Identification System (AIS) provides the potential to further investigate the size and the governing factors of the domain. This investigation revisits and proposes a method using data based on 600,000 ship encounters at 36 locations. It is concluded that the ship domain has the shape of an ellipse with half axis radii of 0.9 and 0.45 nautical miles. However, there are two factors that greatly affect the ship domain: how large the area is that is used to gather vessel intersections and whether they are constrained by water depth. In contradiction to some previous research, it is found that the ship domain is unrelated to the length of the ship.

Vulnerability of satellite-based navigation signals to intentional and unintentional interference calls for a high-level overview of Global Navigation Satellite System (GNSS) threats occurring globally to understand the magnitude and evolution of the problem. Therefore, a mechanism needs to be developed whereby disparate monitoring systems will be capable of contributing to a common entity of basic information about the threat scenarios they experience. This paper begins with a literature survey of 37 state-of-the-art GNSS threat monitoring systems, which have been analysed based on their respective operational features - constellations monitored and whether they possess the capability to perform interference-type classification, spoofing detection, and interference localisation. Also described is a comparative analysis of four GNSS threat reporting formats in use today. Based on these studies, the paper describes the Horizon2020 Standardisation of GNSS Threat Reporting and Receiver Testing through International Knowledge Exchange, Experimentation and Exploitation (STRIKE3) proposed integrated threat monitoring demonstration system and related standardised threat reporting message, to enable a high-level overview of the prevailing international GNSS threat scenarios and its evolution over time.

Precise autonomous navigation remains a substantial challenge to all underwater platforms. Inertial Measurement Units (IMU) and Doppler Velocity Logs (DVL) have complementary characteristics and are promising sensors that could enable fully autonomous underwater navigation in unexplored areas without relying on additional external Global Positioning System (GPS) or acoustic beacons. This paper addresses the combined IMU/DVL navigation system from the viewpoint of observability. We show by analysis that under moderate conditions the combined system is observable. Specifically, the DVL parameters, including the scale factor and misalignment angles, can be calibrated in-situ without using external GPS or acoustic beacon sensors. Simulation results using a practical estimator validate the analytic conclusions.

With the existing GPS, the replenishment of GLONASS and the launching of Galileo there will be three satellite navigation systems in the future, with a total of more than 80 satellites. So it can be expected that the performance of the global navigation satellite system (GNSS) will be greatly improved, especially in urban environments. This paper studies the potential benefits of GPS/GLONASS/Galileo integration in an urban canyon – Hong Kong. The navigation performances of four choices (GPS alone, GPS+GLONASS, GPS+Galileo and GPS+GLONASS+Galileo) are evaluated in terms of availability, coverage, and continuity based on simulation. The results show that there are significant improvements in availability, coverage and continuity, by using GPS+GLONASS+Galileo compared with the other choices. But the performance is still not good enough for most navigation applications in urban environments.

Managing the transit vessel traffic in the Strait of Istanbul is a highly complex operation since vessels, weather and water conditions, and a set of regulations affect its operation significantly. At the present time, the Vessel Traffic Services (VTS) operators manage the traffic based on some fundamental rules. After discussions with the VTS, in this report, we present a mathematical formulation of the scheduling process currently in place and validate it by comparing its results with scheduling decisions made by the operators in some days of 2005. The results are highly promising. The fundamental philosophy of the algorithm is to schedule the vessels with highest waiting time first while giving priority to large vessels carrying dangerous cargo. Our goal has been to incorporate the algorithm into a simulation model designed to be used for risk analysis purposes. The proposed algorithm can be slightly altered and used for traffic scheduling in other waterways as well.

The algorithm flow of an inertial-based Pedestrian Navigation System (PNS) can be divided into a trajectory-generation stage and trajectory-calibration stage. The Zero-velocity UPdaTe (ZUPT)-aided Extended Kalman Filter (EKF) algorithm is commonly used to resolve the trajectory of a walking person, but it still suffers from long-term drift. Many methods have been developed to suppress these drifts and thus to calibrate the trajectory generated by the previous stage. However, these methods have certain requirements, such as explicit map information or frequent location revisits, which are hard to satisfy in such situations as Search and Rescue (SAR) operations. A new approach is proposed in this paper that requires no explicit presupposition. This approach is based on a particle filter framework, with the weight of particles being adaptively adjusted according to the a priori knowledge of building structures and human behaviours. The distribution of particle weights is designed with awareness of the regular structures of buildings. The time-varying parameter of the distribution is acquired from a Hidden Markov Model (HMM) based on the foregoing odometry, which has a close relation with human behaviour. HMM is trained offline based on samples acquired in advance. Many real-world experiments under various scenarios were performed, and the results indicate good accuracy and robustness of the proposed approach.

Application of map-matching techniques to GPS positions can provide accurate vehicle location information in challenging situations. The Hidden Markov Model (HMM) is a statistical model that is well known for providing solutions to temporal recognition applications such as text and speech recognition. This paper introduces a novel map-matching algorithm based on HMM for GPS-based wheelchair navigation. Given GPS positions, a hidden Markov chain model is established by using both geometric data and the topology of sidewalk segments. The map-matching algorithm employs the Viterbi algorithm to estimate correct sidewalk segments as hidden states in a HMM in order to match GPS trajectory on the corresponding segment sequence. The HMM-based map-matching algorithm was validated on a campus sidewalk network for wheelchair navigation. The results show an improvement in tracking a wheelchair in dense urban conditions both in accuracy and in computational time.

Single-frequency Precise Point Positioning (PPP) using a Global Navigation Satellite System (GNSS) has been attracting increasing interest in recent years due to its low cost and large number of users. Currently, the single-frequency PPP technique is mainly implemented using GPS observations. In order to improve the positioning accuracy and reduce the convergence time, we propose the combined GPS/GLONASS Single-Frequency (GGSF) PPP approach. The approach is based on the GRoup And PHase Ionospheric Correction (GRAPHIC) to remove the ionospheric effect. The performance of the GGSF PPP was tested using both static and kinematic datasets as well as different types of precise satellite orbit and clock correction data, and compared with GPS-only and GLONASS-only PPP solutions. The results show that the GGSF PPP accuracy degrades by a few centimetres using rapid/ultra-rapid products compared with final products. For the static GGSF PPP, the position filter typically converges at 71, 33 and 59 minutes in the East, North and Up directions, respectively. The corresponding positioning accuracies are 0·057, 0·028 and 0·121 m in the East, North and Up directions. Both positioning accuracy and convergence time have been improved by approximately 30% in comparison to the results from GPS-only or GLONASS-only single-frequency PPP. A kinematic GGSF PPP test was conducted and the results illustrate even more significant benefits of increased accuracy and reliability of PPP solutions by integrating GPS and GLONASS signals.