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In the last years considerable emphasis has been placed on safety at sea. There is the maritime security and surveillance system whose main aim is to execute tasks in the interests of maritime safety and to react in case of emergency. They are monitored by networks of radar stations. On such areas we obtain a lot of navigation data which could be used to improve ship’s parameters (position), using know in geodesy modern M-estimation methods. Simultaneous acquisition of navigational information from many independent radar stations will render it possible to obtain a more accurate ship position in marine traffic surveillance systems in relation to the calculated position. A position expected in an adjustment calculus is received from a watch officer. It is burdened with a fallacy of navigation systems and the quality of marking ship’s route on a map. In the case of navigational-parameter measurements used for depicting ship position, one can obtain incorrect results due to a disturbance in the measurement process. In extreme cases, such erroneous data could significantly differ from the anticipated results. Deviating observations could significantly influence the values of measurement results. In order to eliminate the determination of erroneous measurements, one could use resistant estimation methods with suitably selected attenuation functions. The accuracy of a determined position will not be better than the capabilities of the device used. Adjustment gives the possibility of eliminating or minimizing human errors as well as the errors in the indications of navigational devices. This paper presents the latest robust estimation methods using Danish attenuation function for adjustment of navigational observation, using radar observation.
In survey data, an observation is considered influential if it is reported correctly and its weighted contribution has an excessive effect on a key estimate, such as an estimate of total or change. In previous research with data from the U.S. Monthly Retail Trade Survey (MRTS), two methods, Clark Winsorization and weighted M-estimation, have shown potential to detect and adjust influential observations. This article discusses results of the application of a simulation methodology that generates realistic population time-series data. The new strategy enables evaluating Clark Winsorization and weighted M-estimation over repeated samples and producing conditional and unconditional performance measures. The analyses consider several scenarios for the occurrence of influential observations in the MRTS and assess the performance of the two methods for estimates of total retail sales and month-to-month change.
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.
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. Czaplewski K., Świerczyński S. 2015a M-Estimation as a Tool Supporting a Vessel Traffic Controller in The VTS System , Polish Maritime Research no. 3(87) 2015 Vol. 22; pp. 3–13, Gdańsk 6. Czaplewski K., Świerczyński S. 2015b, Determining the Accuracy of Ship Position as a function of Radar Bearing. 15th IAIN World Congress in Prague, IEEE Full Papers, 978-1-4673-7634-1/15/2015, pp. 42–47, Praha 7. Czaplewski K., Wąż M. 2017 Improvement in Accuracy of Determining a Vessel’s Position with the Use of Neural Networks and Robust M-Estimation . Polish Maritime Research 1 (93
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