On propagation effects in Maritime Situation Awareness: Modelling the impact of North Sea weather conditions on the performance of AIS and coastal radar systems

Abstract

This thesis studies the environmental impact on radio wave propagation of the Automatic Identification System (AIS) and coastal radar systems in the operational area of the Netherlands Coastguard, i.e., the exclusive economical zone (EEZ) of the Netherlands. In this part of the North Sea, the coastguard monitors marine traffic to maintain a safe and secure environment. For their situation awareness, they are depending on (Class A) AIS and (X-band) radar. However, the operators of these sensor systems often experience abnormal effects such as coverage gaps and different detection ranges for AIS and radar. An important and strongly fluctuating cause of these effects is the environmental impact on radio wave propagation. Therefore, the weather conditions on the North Sea and the impact of these different conditions are analysed and modelled.

In general, five common propagation conditions are known: standard atmosphere, evaporation ducts, standard surface ducts, surface-based ducts, and elevated ducts. The effects of these conditions and their occurrences on the North Sea were studied for AIS and radar.

It was found that elevated and surface ducts - most prominent during spring and summer - extend both AIS and radar detection ranges, whereas evaporation ducts - strongest at the end of summer - were found to only extend radar detection ranges. Standard atmospheric conditions lead, for both systems, to minimum detection ranges.

The modelling in this thesis is a proof of concept for the coastguard to make a forecast of the coverage of their systems on a daily basis, by using Numerical Weather Prediction (NWP) data. Such a daily forecast will support the coastguard in the deployment of mobile detection units, such as ships and aircraft. The modelling also enables operators to understand why targets appear either on AIS or radar, thus preventing that signals are wrongly considered false or suspicious.