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Determination of AIS Position Accuracy and Evaluation of Reconstruction Methods for Maritime Observation Data

机译：确定海洋观测数据重建方法的AIS位置准确度和评估

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Automatic Identification System (AIS) increasingly serves as the primary sensor for decision making. But the provided information can be manipulated, and the signal can even be manually disabled to hide illegal activities. In addition, the quality of the AIS data depends strongly on the quality of the sensors installed on the vessel. To determine the accuracy of AIS position data, the paper will compare AIS data with associated radar tracks. The radar data is assumed to be ground truth so that the accuracy of AIS can be determined. In addition, various existing AIS interpolation approaches are discussed and executed on a common representative dataset with over 6.2 million data points of the German Bight. This allows to make meaningful statements about the quality of the methods when interpolating AIS data. Overall, it was revealed that the mean discrepancy between AIS and radar data measures about 97.72m. Moreover, some presented approaches can approximate AIS data with higher accuracy than the classical linear interpolation. However, this accuracy is also associated with an increased computation time, so that it should be weighed which interpolation method should be used depending on the use case.
机译：自动识别系统（AIS）越来越多地用作决策的主要传感器。但是可以操纵提供的信息，甚至可以手动禁用信号以隐藏非法活动。此外，AIS数据的质量强烈取决于安装在船上的传感器的质量。为了确定AIS位置数据的准确性，本文将与相关的雷达轨道进行比较AIS数据。假设雷达数据是基础事实，使得可以确定AIS的准确性。此外，在具有超过620万数据点的共同代表数据集上讨论和执行各种现有的AIS插值方法。这允许在内插AIS数据时对方法的质量进行有意义的陈述。总的来说，据透露，AIS和雷达数据之间的平均差异约为97.72M。此外，一些呈现的方法可以近似具有比经典线性插值更高的准确性的AIS数据。但是，这种精度也与增加的计算时间相关联，因此应该重视应根据用例使用哪种插值方法。

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