Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników

Znaleziono wyników: 4

Liczba wyników na stronie
Pierwsza strona wyników Pięć stron wyników wstecz Poprzednia strona wyników Strona / 1 Następna strona wyników Pięć stron wyników wprzód Ostatnia strona wyników

Wyniki wyszukiwania

help Sortuj według:

help Ogranicz wyniki do:
Pierwsza strona wyników Pięć stron wyników wstecz Poprzednia strona wyników Strona / 1 Następna strona wyników Pięć stron wyników wprzód Ostatnia strona wyników
In the 21st century marine navigation has become dominated by satellite positioning systems and automated navigational processes. Today, global navigation satellite systems (GNSS) play a central role in the process of carrying out basic navigational tasks, e.g. determining the coordinates of a vessel’s position at sea. Since satellite systems are being used increasingly more often in everyday life, the signals they send are becoming more and more prone to jamming. Therefore there is a need to search for other positioning systems and methods that would be as accurate and fast as the existing satellite systems. On the other hand, the automation process makes it possible to conduct navigational tasks more quickly. Due to the development of this technology, all kinds of navigation equipment can be used in the process of automating navigation. This also applies to marine radars, which are characterised by a relatively high accuracy that allows them to replace satellite systems in performing classic navigational tasks. By employing M-estimation methods that are used in geodesy as well as simple neural networks, a software package can be created that will aid in automating navigation and will provide highly accurate information about a given object’s position at sea by making use of radar in comparative navigation. This paper presents proposals for automating the process of determining a vessel’s position at sea by using comparative navigation methods that are based on simple neural networks and geodetic M-estimation methods
In order to improve maritime safety and the efficiency of vessel traffic, systems supervising vessel traffic, i.e. VTS (Vessel Traffic Service), started to be created. These systems are aimed to control vessel traffic in waters where traffic congestion, a large concentration of vessels or the presence of navigational hazards creates a risk of collision or stranding. VTS systems constitute maritime safety centres and they must be equipped with appropriate devices in order to be fully functional. Among devices that provide information about vessels are coastal radar stations which are located around a monitored sea area. This kind of spatial arrangement of these stations can be used to simultaneously obtain information about every vessel, but such observations may be fraught with serious errors. Therefore, the estimation methods that are employed and developed in geodesy can be used to improve the accuracy with which a vessel’s position is determined. The Interactive Navigational Structure, i.e. IANS, is an example of how these methods can be applied in navigation; this term has already been introduced into the literature (Czaplewski, 2004). The text below presents the theoretical assumptions underlying the use of IANS as a tool supporting a vessel traffic controller using the VTS system in his/her work. This presentation is supported by a numerical test that was performed in the waters of the Bay of Gdańsk which are covered by the VTS system
The main aim of this paper is to assess the possibility of using non-conventional geodetic estimation methods in maritime navigation. The research subject of this paper concerns robust determination of vessel’s position using a method of parameters estimation in the split functional model (Msplit estimation). The studies performed will help in finding out if and in which situations the application of Msplit estimation as the method for determining vessel’s position is beneficial from the perspective of navigation safety. The results obtained were compared with the results of traditional estimation methods, i.e. least squares method and robust M-estimation
The main source of information on the situation across the sea basins used by operators of shipping monitoring systems is a network of coastal radar stations. Presently, it is possible to gather navigational information from many individual radar stations simultaneously, which may be used for improving the accuracy of vessel position fixing. However, without making other estimates, we obtain an inconsistent image comprising multiple echoes of the same ship, and as such it is impossible to say which echo presents the vessel on the move. Another problem is the method of performing radar observations, which significantly affects the accuracy of position fixing. The estimated radar distance is encumbered with a gross error in the case of large vessels, as the position of a large vessel is not the same as the position of the edge of the radar echo to which the estimation is made. In this paper, the authors present a method to adjust the measured radar distance. The proposed method may be automated easily, which would significantly enhance VTS positioning processes.
Pierwsza strona wyników Pięć stron wyników wstecz Poprzednia strona wyników Strona / 1 Następna strona wyników Pięć stron wyników wprzód Ostatnia strona wyników
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.