Simulation and Analysis of Sea Surface Electromagnetic Bias for Interferometric Imaging Radar Altimeter

Sea surface electromagnetic (EM) bias is one of the key factors that affects the accuracy of sea surface height (SSH) measurements by altimeters. The received echo by altimeter from sea surface is indeed the integration of backscattering from all the small facets within a pulse-limited footprint, which is largely modulated by the positions of facets. The facets in the troughs contribute much stronger scattering to the echo, so the half-power position of the echo waveform does not reflect the true SSH, i.e., the EM bias in SSH measurement exists. The EM bias correction of conventional altimeters is usually based on the dependencies of wind speed and significant wave height (SWH) on the EM bias. However, this method may not be suitable for interferometric imaging radar altimeter (InIRA) with wide swath and small incidence angles, such as the Tiangong-2 (TG2) launched in 2016 and the Surface Water and Ocean Topography (SWOT) launched in 2022. This is because conventional altimeters use nadir-looking echo waveforms to measure SSH along the track, with a footprint diameter of approximately 2–7km, for InIRA however, e.g., SWOT, consisting of two distinct 50km swaths, provides measurements with a spatial resolution of 1km for the ocean (after on-board processing). This paper aims to investigate the impact of EM bias regarding to InIRA. In this work, the ocean wave height fields with various wind speeds are generated based on the Pierson-Moskowitz (PM) spectrum and Fast Fourier Transforms (FFTs). Subsequently, the measurement procedure of InIRA for calculating SSH is simulated. Finally, the influence of wind speed and SWH on EM bias of InIRA is analyzed and the fitted functions are derived to describe the relationship between EM bias, wind speed, and SWH with various incidence angles. The results indicate that higher wind speeds and smaller incidence angles will lead to greater EM bias in InIRA measurements. Although this work is done based on simulation, the approach to derive the analytical formula for EM bias correction can be adopted fitting to real SSH measurements based on dedicated calibration procedure.