Enhanced Wind Turbine Detection through Radar and Radiometric Sensor Fusion

This paper introduces an overview of a novel sensor fusion model for identifying wind turbines (WTs) that cause interference in polarimetric Doppler weather radar measurements. It is important to acknowledge that the characteristics of WTs, as defined by their radar cross section (RCS), have a substantial effect on radar performance. This is because the RCS of WTs leads to the introduction of multidimensional interference effects, which ultimately influence radar measurements. This interference is due to the incident electromagnetic fields that it interacts with a WT, which, in turn, generates both static and dynamic effects. In the realm of electromagnetic wave-matter interactions, the effective permittivity e f f is composed of two significant aspects: the real part varepsilon prime and the imaginary part varepsilon prime prime. In this context, passive satellite, also known as a radiometer provides sensor data (e.g. Sentinel-2 (S2)) that will be employed to accurately identify WTs causing interference to within the radar data. This is because the different effects of the real and imaginary components in metallic objects and the Earth's surface can be utilized to derive distinct radiometric satellite observables from the given S2 data. These radiometric observables lend themselves to serve as novel Wind Turbine Indices (WTI). Additionally, physical quantities such as emissivity epsilon λ and albedo rho albedo, which describe thermal radiation properties and reflectivity of surfaces, will be evaluated and applied to WT detection.