Presentation + Paper
14 November 2021 Determination of the coastal edge using on-board radar
Author Affiliations +
Abstract
The definition of the coastal edge that defines the outline of the coastline, is one of the main tasks in the drafting of digital maps. The solution to this problem is extremely important for maritime navigation. It is important to constantly monitor the outlines of coastlines in connection with natural disasters that can change the coastal edge, such as landslides, tsunami, ice melting, etc. This, in turn, can lead to dangerous consequences for vessels carrying out civil transportation and humanitarian assistance in waters affected by natural disasters. The solution to this problem is of particular importance for archipelago countries such as Indonesia, England, etc The most common methods for determining the coastline are radar-optical methods using opticalradar systems located on-board unmanned small aerial vehicles flying according to predetermined programs. This makes it possible to determine the outlines of the coastline in an automatic (automated) mode, in fact, not depending on weather conditions, and to receive operational information in realtime, practically without time delays The paper considers and analyzes the algorithm for determining the coastal edge using smallsized radar stations located on small unmanned aerial vehicles. This allows you to fully automate the monitoring process. Depending on the characteristics of the on-board equipment and its operating modes, the accuracy of determining the land-sea edge can reach one and a half meters.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gysberth Maurits Wattimena, Dmitry Shepeta, and Victor Isakov "Determination of the coastal edge using on-board radar", Proc. SPIE 11914, SPIE Future Sensing Technologies 2021, 119140D (14 November 2021); https://doi.org/10.1117/12.2603944
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KEYWORDS
Smoothing

Radar

Reflection

Signal processing

Modeling

Natural disasters

Digital filtering

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