Journal of Navigation 

About: Journal of Navigation is an academic journal published by Cambridge University Press. The journal publishes majorly in the area(s): Global Positioning System & GNSS applications. It has an ISSN identifier of 0373-4633. Over the lifetime, 3050 publications have been published receiving 34527 citations.

A statistical study of ship domains

Abstract: The thesis is an attempt to establish the water area required by any one ship for safe and efficient navigation. The concept of a ship domain has been considered, which may be defined as the effective area around a ship which a navigator would like to keep free with respect to other ships and stationary objects. This area will not be the same for all ships but will depend on a variety of factors such as speed, size of ship and density of traffic among others. The first part of the project was concerned with the collection of data from two separate sources: one being the performance of ships' officers in collision avoidance exercises on a marine radar simulator and the second being marine traffic surveys conducted in the Sunk area of the North Sea, The collection of data on ship movements and their processing for analysis by computer comprised the early work of the thesis. The next section of work was concerned with the development of a technique for evaluating the size of the domain and in particular the range of the domain boundary from the ship referred to as the domange. Very little work appears to have been done on this topic previously so several possibilities were considered before a decision was made as to the most suitable technique. Once this had been established results were obtained for a variety of conditions such as different sea area, length of ship and experience of the navigator as well as those previously mentioned and others. The final part of the thesis considers possible applications of the results in a variety of situations which are of current and future interest in marine traffic studies.

Automatic Identification System (AIS) : data reliability and human error implications

Abstract: This paper examines the recent introduction of the AIS to the ship's bridge and its potential impact on the safety of marine navigation. Research has shown that 80 to 85% of all recorded maritime accidents are directly due to human error or associated with human error. Safety is an important element of marine navigation and many people at different levels are involved in its management. The safe and efficient performance of joint systems, is heavily dependent upon how functions are allocated between the human and the machine. This paper investigates different regulations, supervision for proper use, training, and management of AIS users. It uses previous research and three separate AIS studies to identify problems. The potential of the AIS to cause problems is analysed. The classic human factor “Swiss Cheese” Model of system failure has been modified for the AIS to investigate a possible accident trajectory. The paper then concludes with recommendations and suggestions for improvements and further work.

Autonomous ship collision avoidance navigation concepts, technologies and techniques

Abstract: This study provides both a spherical understanding about autonomous ship navigation for collision avoidance (CA) and a theoretical background of the reviewed work. Additionally, the human cognitive abilities and the collision avoidance regulations (COLREGs) for ship navigation are examined together with water based collision avoidance algorithms. The requirements for autonomous ship navigation are addressed in conjunction with the factors influencing ship collision avoidance. Humans are able to appreciate these factors and also perform ship navigation at a satisfactory level, but their critical decisions are highly subjective and can lead to error and potentially, to ship collision. The research for autonomous ship navigation may be grouped into the classical and soft computing based categories. Classical techniques are based on mathematical models and algorithms while soft-computing techniques are based on Artificial Intelligence (AI). The areas of AI for autonomous ship collision avoidance are examined in this paper are evolutionary algorithms, fuzzy logic, expert systems, and neural networks (NN), as well as a combination of them (hybrid system).

Improving Adaptive Kalman Estimation in GPS/INS Integration

Abstract: The central task of GPS/INS integration is to effectively blend GPS and INS data together to generate an optimal solution. The present data fusion algorithms, which are mostly based on Kalman filtering (KF), have several limitations. One of those limitations is the stringent requirement on precise a priori knowledge of the system models and noise properties. Uncertainty in the covariance parameters of the process noise (Q) and the observation errors (R) may significantly degrade the filtering performance. The conventional way of determining Q and R relies on intensive analysis of empirical data. However, the noise levels may change in different applications. Over the past few decades adaptive KF algorithms have been intensively investigated with a view to reducing the influence of the Q and R definition errors. The covariance matching method has been shown to be one of the most promising techniques. This paper first investigates the utilization of an online stochastic modelling algorithm with regards to its parameter estimation stability, convergence, optimal window size, and the interaction between Q and R estimations. Then a new adaptive process noise scaling algorithm is proposed. Without artificial or empirical parameters being used, the proposed adaptive mechanism has demonstrated the capability of autonomously tuning the process noise covariance to the optimal magnitude, and hence improving the overall filtering performance.

Positional Accuracy of Assisted GPS Data from High-Sensitivity GPS-enabled Mobile Phones

Abstract: Utilizing both Assisted GPS (A-GPS) techniques and new high-sensitivity embedded GPS hardware, mobile phones are now able to achieve positioning in harsh environments such as urban canyons and indoor locations where older embedded GPS chips could not. This paper presents an empirical analysis of the positional accuracy of location data gathered using a high-sensitivity GPS-enabled mobile phone. The performance of the mobile phone is compared to that of regular recreational grade GPS receivers. Availability of valid GPS position fixes on the mobile phones tested was consistently close to 100% both outdoors and indoors. During static outdoor testing, positions provided by the mobile phones revealed a median horizontal error of between 5·0 and 8·5 m, substantially larger than those for regular autonomous GPS units by a factor of 2 to 3. Horizontal errors during static indoor testing were larger compared to outdoors, but the difference in accuracy between mobile phones and regular GPS receivers was reduced. Despite the modest performance of A-GPS on mobile phones, testing under various conditions revealed that very large errors are not very common. The maximum horizontal error during outdoor testing never exceeded 30 metres and during indoor testing never exceeded 100 metres. Combined with the relatively consistent availability of valid GPS position fixes under varying conditions, the current study has confirmed the reliability of A-GPS on mobiles phones as a source of location information for a range of different LBS applications.