The main aim of the project was the training and research of young scientists in the area of multi-parameter polarimetry at partner organisations spread all over Europe (i.e. DLR, TU Chemnitz and Definiens Imaging GmbH, Germany; University of Essex, UK; DDRE, Denmark; UPC, Spain; MOTHESIM and University of Rennes, France; JRC, Italy). The scientific activities of the network fall into three main areas dealing with sensor systems and measured data, the underlying physics and scattering models, parameter retrieval and product generation.
The focus of modelling atmospheric effects was on the scattering of hydrometeors, particularly rain drops. The main purpose is not only to have a coherent model for simulating weather radar data, but also to create a link between observations by weather radar systems and SAR systems. Polarimetric propagation effects play an important role for both systems, and, hence, the model can be used to predict or describe the influence of propagation through a medium containing rain drops for polarimetric radars, regardless of whether they are ground-based or airborne/spaceborne. Raindrops are oblate scatterers, where the oblateness increases with the size of the rain drop, and thus rainfall produces anisotropic scattering, which can be measured with polarimetric radars. One particular problem occurs, because the four elements of the scattering matrix are not all measured at the same time but with a certain time delay, which is usually around 1 ms. During this time, the observed scattering volume (containing falling rain drops) changes and, thus, decorrelation will be seen.
Using model results and experience drawn from the literature, phase delays and amplitude effects on radar data can be predicted. Special attention has been given to the impact of such effects on the processing of SAR images. Phase changes due to atmospheric distortions have a similar behaviour to motion errors of the sensor platform and thus might not be separated from such additional error sources.
With regard to polarimetric decomposition theorems, two signal processing approaches have been applied for the first time to fully polarimetric SAR and weather radar signatures. Considerable attention is paid to the eigenvectors of the covariance matrix.