Clustering methods that use a similarity measurement for evaluating vessel trajectories are important for mining spatial distribution information in water transportation. To better measure the similarity of vessel trajectories, a novel similarity measure is proposed based on the dynamic time warping distance, which considers the course change of track points and the meaning at the route level. Parallel experiments were conducted based on a month of Automatic Identification System (AIS) data collected from the Zhoushan Islands area, China. After evaluation of the accuracy and the cluster degree, the novel measure demonstrated its capabilities for distinguishing different vessel trajectories and detecting similar vessel trajectories with high accuracy and has a better performance compared to some existing methods.

Interoperability of GNSS Open Services is a significant trend in the development of all the satellite navigation systems, and its performance will directly affect the users' security and reliability. Therefore, the monitoring and assessment of GNSS Open Services has become a focus of attention for all providers and users of GNSS. In this paper the elements and methods for the monitoring and assessment of GNSS Open Services are investigated first. Then the schemes designed for an international GNSS Monitoring and Assessment System (iGMAS) are proposed. The schemes are based on omni-directional antennas, multi-beam antennas and a high-gain paraboloid antenna to achieve Quadruple-overlap and Single-overlap coverage and sophisticated analysis respectively. Moreover, the scheme for the deployment of world-wide monitoring stations is also proposed. Finally, some related works that have been conducted to monitor and assess Beidou Open Services are introduced, which verifies the feasibility of the proposed system.

This study develops a Zero-Inflated Negative Binomial (ZINB) regression model to evaluate the factors influencing the loss of human life in shipping accidents using ten years' ship accident data in the South China Sea. The ZINB regression model results show that the expected loss of human life is higher for collision, fire/explosion, contact, grounding, hull damage, machinery damage/failure and capsizing accidents occurring in adverse weather conditions during night periods. Sinking can cause the highest loss of life compared to all other accident types. There are fewer fatalities and missing people when the ship involved in an accident is moored or docked. The results also reveal that the loss of human life is associated with shipping accidents occurring far away from the coastal area/harbour/ports. The results of this study are beneficial for policy-makers in proposing efficient strategies to reduce shipping accident casualties in the South China Sea.

Future air traffic management will require a variety of automated decision support tools to provide conflict-free trajectories and their associated error margins. The ability to correctly forecast aircraft trajectories, i.e. trajectory prediction, is the central component of such automated tools, which will enable continued provision of safe and efficient services in increasingly congested skies. Current approaches for trajectory prediction, available in the open literature, make a number of assumptions in order to simplify the mathematical models of aircraft motion. Furthermore, many existing methods perform three-dimensional trajectory prediction, in which information on expected times of arrival at significant points along the intended aircraft route is not considered. This results in inaccurate trajectories not suitable for conflict detection and resolution. This paper presents a novel four-dimensional trajectory prediction scheme that makes full use of data on expected times of arrival. A three dimensional point-mass model for a standard civil aircraft is used to emulate aircraft dynamics, while the aircraft operating mode is characterised through a set of discrete variables. The aircraft performance model used relies on the EUROCONTROL Base of Aircraft Data (BADA) set and the computed trajectory accounts for the effects of wind. Inputs include navigation data and aircraft intent information, which unambiguously define the trajectory to be computed according to the flight plan. In the proposed model, aircraft intent information is summarised in a simple, but effective, set of instructions contained in a Flight Script. Furthermore, two key innovations to trajectory prediction are introduced. Firstly, a novel scheme to emulate the control system used for aircraft lateral guidance is proposed and secondly, on the basis of aircraft intent information, a new procedure to estimate speed is presented. The performance of the enhanced trajectory model proposed is quantified using a detailed operational dataset (real flight data) captured in a European airspace. The results show that, over an extended time-horizon, the enhanced model is more accurate than two representative existing methods, and that it is suitable for reliable trajectory prediction.

Recently new location technologies have emerged that can be employed in modern advanced navigation systems. They can be employed to augment Global Navigation Satellite System (GNSS) positioning techniques and dead reckoning as they offer different levels of positioning accuracies and performance. An integration of other technologies is especially required in indoor and outdoor-to-indoor environments. The paper gives an overview of the newly developed ubiquitous positioning technologies and their integration in navigation systems. Furthermore two case studies are presented, i.e., the improvement of land vehicle safety using Augmented Reality (AR) technologies and pedestrian navigation services for the guidance of users to certain University offices. In the first case study the integration of map matching into a Kalman filter approach is performed (referred to as “Intelligent Vehicle Navigation”) and its principle is briefly described. This approach can also be adapted for the pedestrian navigation service described in the second case study.

For the integrated navigation system, the correctness and the rapidity of fault detection for each sensor subsystem affects the accuracy of navigation. In this paper, a novel fault detection method for navigation systems is proposed based on Gaussian Process Regression (GPR). A GPR model is first used to predict the innovation of a Kalman filter. To avoid local optimisation, particle swarm optimisation is adopted to find the optimal hyper-parameters for the GPR model. The Fault Detection Function (FDF), which has an obvious jump in value when a fault occurs, is composed of the predicted innovation, the actual innovation of the Kalman filter and their variance. The fault can be detected by comparing the FDF value with a predefined threshold. In order to verify its validity, the proposed method is used in a SINS/GPS/Odometer integrated navigation system. The comparison experiments confirm that the proposed method can detect a gradual fault more quickly compared with the residual chi-squared test. Thus the navigation system with the proposed method gives more accurate outputs and its reliability is greatly improved.

With the European Commission (EC) and European Space Agency's (ESA) plans to develop a new satellite navigation system, Galileo and the modernisation of GPS well underway the integrity of such systems is as much, if not more, of a concern as ever. Receiver Autonomous Integrity Monitoring (RAIM) refers to the integrity monitoring of the GPS/Galileo navigation signals autonomously performed by the receiver independent of any external reference systems, apart from the navigation signals themselves. Quality measures need to be used to evaluate the RAIM performance at different locations and under various navigation modes, such as GPS only and GPS/Galileo integration, etc. The quality measures should include both the reliability and localizability measures. Reliability is used to assess the capability of GPS/Galileo receivers to detect the outliers while localizability is used to determine the capability of GPS/Galileo receivers to correctly identify the detected outlier from the measurements processed.

Within this paper, the fundamental equations required for effective outlier detection and identification algorithms are described together with the measures of reliability and localizability. Detailed simulations and analyses have been performed to assess the performances of GPS only and integrated GPS/Galileo navigation solutions with respect to reliability and localizability. Simulation results show that, in comparison with the GPS-only solution, the localizability of the integrated GPS/Galileo solution can be improved by up to 270%. The results also indicate an expectation of a considerable increase in the sensitivity to outliers and accuracy of their estimation with the augmentation of the Galileo system with the existing GPS system.

Autonomous vehicles with an ability to trace chemical plumes can be instrumental in tasks such as detection of unexploded ordnance, search for undersea wreckage and environmental monitoring. As a consequence, use of autonomous vehicles to perform chemical plume tracing has received an increasing interest from the research community in recent years. Owing to the diversity of applications and ambient fluid environment of the plumes, there are numerous plume tracing strategies and approaches. This paper reviews two main approaches and a number of strategies that have been successfully implemented to track air or water borne plumes in order to locate odour sources using autonomous vehicles. The first strategy considered is the biomimetic approach that offers excellent models for the development of robotic systems. Strategies inspired by lobsters and bacterium are the main focus in this study. The second scheme considers parallelization of the search procedure by employing a multi-robot approach. This approach has the advantage of utilising a group of smaller and simpler communicating robots which are capable of performing a collaborative search of the plume.

Increased fuel costs necessitate a careful consideration of consumption when planning voyages trans-ocean. A model is formulated whereby ship response algorithms are matched with forecast environmental conditions expected for the duration of a voyage. A discrete system allows an optimization routine to minimize fuel costs for a trans-atlantic passage, using dynamic programming techniques.

These are simulated by using an on-board boosted micro-computer. The results are discussed and limitations of the system considered.

Two main concepts in mathematical modelling of ship encounters have been proposed by Davis. The first, the ‘domain’, was an adaptation of a concept originally introduced by Goodwin, who defined the domain as the ‘area about own-ship that a navigator wished to keep free with respect to ships and other stationary objects’. The second, the ‘arena’, conceived by Davis, is the area around the domain which when infringed causes the mariner to consider whether to make a collision-avoidance manoeuvre. Thus, in a computer model, when a vessel enters the arena the computer analyses the situation and, depending on the severity of the threat, makes a collision-avoidance manoeuvre.

Goodwin's domain was divided into three sectors corresponding to the ‘giveway’, the ‘stand-on’ and the ‘overtaking’ regions as defined by the relative velocity of approach. The domain was derived from radar films of ship tracks and records of radar simulator experiments. Davis smoothed the sectored domain to a circle with own-ship off-centred astern and to port, and the weighting of each of the sectors retained. Davis's domain had a solid theoretical grounding; the arena, however, was simply a larger version of the smoothed domain. Its size and position were obtained by means of a well-distributed questionnaire. It served its purpose in the model, but lacked any real validation.

One problem with the Davis arena was its inability automatically to take into account different velocities, both of own-ship and of targets.

In this paper, a novel method of sensor based pedestrian dead reckoning is presented using sensors mounted on a shoe. Sensor based systems are a practical alternative to global navigation satellite systems when positioning accuracy is degraded such as in thick forest, urban areas with tall buildings and indoors. Using miniature, inexpensive sensors it is possible to create self-contained systems using sensor-only navigation techniques optimised for pedestrian motion. The systems developed extend existing foot based stride measurement technology by adding the capability to sense direction, making it possible to determine the path and displacement of the user. The proposed dead-reckoning navigation system applies an array of accelerometers and magneto-resistive sensors worn on the subject's shoe. Measurement of the foot's acceleration allows the precise identification of separate stride segments, thus providing improved stride length estimation. The system relies on identifying the stance phase to resolve the sensor attitude and determine the step heading. Field trials were carried out in forested conditions. Performance metrics include position, stride length estimation and heading with respect to a high accuracy reference trajectory.

The Hatch filter is a code-smoothing technique using integrated carrier phase observations. It is an easy technique that non-experts can use to reduce receiver noise on the pseudorange. This paper suggests a new algorithm for the optimal Hatch filter whose smoothing window width varies adaptively depending on the regional, diurnal and seasonal ionospheric variation and satellite elevation angle. We consider both quiet and storm conditions of the ionosphere. Using the well-known quiet ionospheric model, a conservative boundary value for ionospheric storm and the receiver noise statistics function of the satellite elevation angle, this algorithm can mathematically solve the optimal averaging constant for each satellite in every epoch. From a 24 hr data process result and real-time experiment, we found that the position accuracy of the optimal Hatch filter is better and more robust than that of the traditional Hatch filter. The optimal Hatch filter algorithm and its results are expected to provide a new solution for a single-frequency DGPS receiver and a thorough understanding of the relationship between the position error and the averaging constant. Furthermore, a DGPS user who applies this algorithm to a low-cost single-frequency receiver can obtain a more accurate and robust position result than via the classical Hatch filter.

The safety of maritime transportation has become increasingly important in recent decades. In this paper, a decision model (a multi-objective and multi-layer fuzzy optimisation model) for navigation risk in different sea areas is established. This is done according to the evaluation index system based on relative data extracted and analysed from Automatic Identification Systems (AIS) information and the multi-objective and multi-layer fuzzy optimisation theory. Then, sorted by an optimal relative membership degree vector and calculated from lower layer to higher layer, the sea areas which have higher navigation risk are selected. Finally, the decision model is shown to be scientific and practical since the results from it are basically consistent with real traffic in Chengshantou waters and the results from the fuzzy comprehensive evaluation model. With the decision model, navigation risk judgments in different sea areas can be offered. It can also provide decision making references to the design of ship routing systems, the layout of search and rescue sites, the configuration of rescue forces and the administration of navigation safety.

Despite the extent of works done on modelling port water collisions, not much research effort has been devoted to modelling collisions at port anchorages. This paper aims to fill this important gap in the literature by applying the Navigation Traffic Conflict Technique (NTCT) to measuring the collision potentials in anchorages and for examining the factors contributing to collisions. Building on the principles of the NTCT, a collision potential measurement model and a collision potential prediction model were developed. These models were illustrated by using vessel movement data of the anchorages in Singapore port waters. Results showed that the measured collision potentials are in close agreement with those perceived by harbour pilots. Higher collision potentials were found in anchorages attached to the shoreline and international fairways, but not at those attached to confined water. Higher operating speeds, larger numbers of isolated danger marks and day conditions were associated with reduction in the collision potentials.

A version of this paper was first presented at the European Navigation Conference 2006, held under the auspices of the RIN at Manchester on 8–10 May 2006.

AIS is the most recent example of a major globally-introduced maritime navigation system. During its evolution, introduction and early in-service life, it has aroused a lot of negative comment. The basis for this negativity is examined, particularly in the light of the real experience that is now being gained by users of the system. The evolution of the AIS concept through the relevant international bodies – IMO, ITU, IALA and IEC – is discussed, together with the type of problems encountered during its introduction. Many of the problems would have been ameliorated if there had been better communication to users of the system. It is argued that the complexity of the system really required mandatory training to be undertaken, in parallel with the installation of the new equipment.

This paper describes the United States Coast Guard's efforts regarding Long Range Identification & Tracking (LRIT) of ships. Among those elements included in the LRIT plan, automatic identification systems (AIS), typically envisioned as a short-range system, may also play a long-range role. AIS vessel tracking may be accomplished through high elevation shore sites allowing reception of AIS signals to nominally 24 nm that loosely puts it in the category of a short-range sensor. Additionally, the US Coast Guard is conducting research and development efforts to determine the feasibility of using AIS receive capability on low earth orbit (LEO) satellites and high altitude, long endurance (HALE) airships or balloons. In parallel with the developing technical capabilities, the US approach with the International Maritime Organization (IMO), and domestic legislation and regulations are also addressed. Finally, a vision for the implementation of LRIT is offered. The paper was presented on 9 November 2004 at Church House, London during the Institute's NAV 04 Conference.

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.

The extended Kalman filter, when employed in the GPS receiver as the navigation state estimator, provides optimal solutions if the noise statistics for the measurement and system are completely known. In practice, the noise varies with time, which results in performance degradation. The covariance matching method is a conventional adaptive approach for estimation of noise covariance matrices. The technique attempts to make the actual filter residuals consistent with their theoretical covariance. However, this innovation-based adaptive estimation shows very noisy results if the window size is small. To resolve the problem, a multilayered neural network is trained to identify the measurement noise covariance matrix, in which the back-propagation algorithm is employed to iteratively adjust the link weights using the steepest descent technique. Numerical simulations show that based on the proposed approach the adaptation performance is substantially enhanced and the positioning accuracy is substantially improved.

The regional ship collision risk assessment for multiple ships in restricted waters is of great significance to the early warning of ship collision risk and the intelligent supervision of maritime traffic. Given the existed method of regional ship collision risk assessment without considering the impact of ship aggregation density, this paper proposes a novel regional ship collision risk assessment method that considers the aggregation density (AD) of the clusters of encounter ships (CES) for intelligent surveillance and navigation. The effectiveness of the proposed method has been examined by the experimental case study in the waters of Xiamen, China, and analysis has been compared with other existed studies to show the advantages of the new proposed algorithm. The results show that the study method can more intuitively and effectively quantify the temporal and spatial distribution of regional collision risks in the restricted sea area. The proposed method can improve the efficiency of traffic management when monitoring the ship collision risks in macroscopic view, and assist the safety of manned and unmanned ship navigation.

Many countries are making increased efforts to improve marine security and safety and develop ship surveillance techniques to satisfy the increasing demands. Space-borne Synthetic Aperture Radar (SAR) delivers high performance day/night all weather capabilities and a space-based Automatic Identification System (AIS) can give near real time and global coverage. Limited by the development of sensors and data processing techniques, the integration of space-borne SAR and AIS has much to offer ship surveillance. State-of-the-art data fusion methods have generally provided satisfactory performance. However, in high-density shipping or high sea-states, performance quality is less assured. This paper firstly investigates improved data association methods. The association methods based on the position feature are improved, and multi-feature-based association methods are proposed. Then, ship identification and tracking by the integration of space-borne SAR and AIS are researched further. Multi-source data fusion strategy is also investigated. Finally, the discussion is presented and the future works are emphasized in the conclusion.