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Wyszukujesz frazę "ship movement prediction" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Two-dimensional coordinate estimation for missing automatic identification system (AIS) signals based on the discrete Kalman filter algorithm and universal transverse mercator (UTM) projection
Autorzy:
Jaskólski, K.
Powiązania:
https://bibliotekanauki.pl/articles/135285.pdf
Data publikacji:
2017
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
AIS
Kalman filter
AIS data estimation
data fusion
ship movement prediction
ship motion tracking
Opis:
Due to safety reasons, the movement of a ship in coastal areas should be monitored, tracked, recorded, and stored. The Automatic Identification System (AIS) is a suitable tool to use in performing these functions. The probability limit for the AIS dynamic data availability can be limited by the lack of a Global Position System (GPS) signal, heading (HDG), and rate of turn (ROT) data in the position report. The unavailability of a data link is an additional limitation. To fill this gap, it is possible to attach the discrete Kalman filter (KF) for the position and course estimation. Coordinate estimation in the absence of a transmission link can improve the quality of the AIS service at Vessel Traffic Service (VTS) stations. This paper has presented the Kalman filtering algorithm to improve the possibilities for ship motion tracking and monitoring in the TSS (Traffic Separation Scheme) and fairways area. More than 570 iterations were calculated and the results have been presented in figures to familiarize the reader with the operating principle of the Kalman filter algorithm.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2017, 52 (124); 82-89
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Algorithms for Ship Movement Prediction for Location Data Compression
Autorzy:
Czapiewska, A.
Sadowski, J.
Powiązania:
https://bibliotekanauki.pl/articles/116761.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
Methods and Algorithms
Ship Movement, Ship Movement Prediction
Location
Location Data Compression
Autoregressive Model (AR)
Autoregressive Moving Average Model (ARMA)
AIS Data
Opis:
Due to safety reasons, the movement of ships on the sea, especially near the coast should be tracked, recorded and stored. However, the amount of vessels which trajectories should be tracked by authorized institutions, often in real time, is usually huge. What is more, many sources of vessels position data (radars, AIS) produces thousands of records describing route of each tracked object, but lots of that records are correlated due to limited dynamic of motion of ships which cannot change their speed and direction very quickly. In this situation it must be considered how many points of recorded trajectories really have to be remembered to recall the path of particular object. In this paper, authors propose three different methods for ship movement prediction, which explicitly decrease the amount of stored data. They also propose procedures which enable to reduce the number of transmitted data from observatory points to database, what may significantly reduce required bandwidth of radio communication in case of mobile observatory points, for example onboard radars.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2015, 9, 1; 75-81
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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