Characterization and Correction of Ionospheric Signals in Low-Frequency Synthetic Aperture Radar Systems

Kurzfassung

Low-frequency Synthetic Aperture Radar (SAR) plays an essential role in efficientlymonitoring geophysical observables such as forest biomass or the state of ice sheets. The penetration capability of the incident electromagnetic waves into volume scatterers allows vertical structure characterization and the detection of non-superficial targets. The principle was demonstrated with L-band (wavelength approx. 21 cm) missions and currently the European Space Agency (ESA) is preparing for the launch of the first time in space P-band (wavelength approx. 69 cm) SAR mission called Biomass. As a primary objective, Biomass aims to estimate the global forest above-ground biomass at high spatial resolution and extensive coverage. The presence of the ionosphere will challenge this task since its dispersive and anisotropic nature introduces distortions in the transmitted and received signals, lowering the quality of the products and leading to the misinterpretation of the data. The amount of distortions depends on the Total Electron Content (TEC) experienced by the radar waves on their two-way path, and they range from time delays and phase errors to a rotation of the polarization plane and changes in the radar cross section known as scintillation. The TEC is a dynamic parameter that varies in time and space so that TEC distributions leave 2-D distortion maps in the images. For the ionospheric calibration processing step, state-of-the-art algorithms were adapted during the development of this thesis, and new ones were further developed for the preparation for the mission. In the absence of spaceborne P-band data, all this work was carried out based on simulations and L-band images from ALOS-PALSAR. This thesis deals with the entire life cycle of the ionospheric signal from the generation, the injection into simulated data, the estimation and correction of data, and finally, the possibility of extracting geophysical parameters from the ionospheric signatures. Accurate but also efficient injection of ionospheric disturbances is a crucial step to develop estimation and correction algorithms in a simulation framework. The ionospheric calibration is divided into two steps: A visualization step, where the TEC is estimated via a distortion map (i.e., defocusing due to phase errors or Faraday rotation across the polarimetric channels), and a correction step, where the inverted TEC is used to compensate the original distortions. In this thesis, several calibration approaches are proposed for different data configurations (quadpol, single-pol or interferometric stacks), and their performance is assessed and compared with each other for different scenarios. The product of the visualization step is unique in the sense that no other ionospheric sensing technology provides such a high resolution and wide coverage of 2-D maps of the ionosphere as SAR does, making it highly attractive to the community that studies small-scale TEC irregularities. For this reason, effort was put into the characterization of residual maps. Finally, as a use case of the exploitation of the ionospheric signature, the capability of estimating the location of the ionospheric irregularities based on scintillation patterns in an ALOS-2/PALSAR-2 dataset is shown. The algorithms developed during this thesis are designed explicitly for P-band SAR data in the Biomass framework. The techniques will be helpful in the commissioning and operational phases of the mission. However, the knowledge and contributions go beyond Biomass. They are worth revisiting with other new L-band systems such as the NASA-ISRO Synthetic Aperture Radar (NISAR) and the development of even lower-frequency radar remote sensing approaches such as the Earth orbiting radar sounder.