Predicting AIS reception using tropospheric propagation forecast and machine learning

Z. Vanche, A. Renaud, A. Napoli
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引用次数: 1

Abstract

The aim of this paper is to present a methodology for modelling and predicting the coverage of an Automatic Identification System (AIS) station based on tropospheric index forecast maps and modelling methods from machine learning. The aim of this work is to cartographically represent the areas in which the AIS signals emitted by ships will be received by a coastal station. This work contributes to the improvement of maritime situational awareness and to the detection of anomalies at sea [1], and in particular to the identification of AIS message falsifications [2] (ubiquity of a vessel by identity theft, falsification of GPS positions and deactivation of AIS).
使用对流层传播预测和机器学习预测AIS接收
本文的目的是提出一种基于对流层指数预测图和机器学习建模方法的自动识别系统(AIS)站覆盖建模和预测方法。这项工作的目的是在地图上表示船舶发出的AIS信号将被沿海站接收的区域。这项工作有助于提高海上态势感知能力,探测海上异常[1],特别是识别AIS信息伪造[2](通过身份盗窃、伪造GPS位置和禁用AIS来无处不在的船只)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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