TITLE:
Simulation Study of GNSS-R-Based Marine Oil Spill Detection Considering Sea Surface Asymmetry
AUTHORS:
Jintao Yu, Bin Wang, Dongmei Song
KEYWORDS:
GNSS-R, Marine Oil Spill, Wind Speed, Delay-Doppler Map
JOURNAL NAME:
Journal of Computer and Communications,
Vol.13 No.6,
June
30,
2025
ABSTRACT: Marine oil spills cause severe ocean pollution. When oil spreads over the sea surface, it hinders optical processes within the ocean and consumes large amounts of dissolved oxygen during decomposition, leading to massive marine life mortality. To mitigate the impact of oil spill disasters, real-time and accurate monitoring is of great significance for protecting the marine ecosystem. Traditional optical and radar remote sensing techniques often suffer from long revisit times, making it difficult to respond swiftly to offshore oil spill incidents, thus exacerbating marine pollution. In contrast, Global Navigation Satellite System Reflectometry (GNSS-R) offers all-weather, real-time monitoring capabilities, making it more suitable for detecting oil spills on the sea surface. This study focuses on the oil spill incident caused by the Symphony cargo ship on April 27, 2021. Considering the asymmetry of the actual sea surface, the bistatic scattering coefficient of the oil-covered sea surface is calculated using the KA-GO model. Combined with the Z-V scattering model and a sea surface/oil slick Mean Square Slope (MSS) model, a Delay-Doppler Map (DDM) reflecting oil spill features is generated. Simulation results demonstrate that DDMs can effectively detect oil spill areas, validating the feasibility of GNSS-R for this application. Furthermore, the study reveals that sea surface wind speed significantly influences simulation results: when wind speed exceeds 2 m/s, the differences in MSS and scattering coefficients between oil-covered and clean sea surfaces become more pronounced, decreasing with higher wind speeds. Finally, CYGNSS (Cyclone GNSS) satellite data is used to verify the consistency of oil spill-induced GNSS-R signal patterns derived from simulation, providing both theoretical and methodological references for applying GNSS-R in marine oil spill monitoring.