Stochastic technique for 2D tomographic reconstruction of rainfall fields through microwave measurements

The general problem of 2D image reconstruction based on a tomographic approach is here explored in a particular case. Exploiting the relationship between microwave attenuation and rainfall intensity in a microwave tomography approach was demonstrated to be a valid possibility for the reconstruction of rainfall fields in limited areas. At each time step, path-integrated attenuation measurements are provided by a set of microwave transmitter-receiver pairs, and two-dimensional Gaussian basis functions are utilized to reconstruct the space-time distribution of the rainfall intensity field. The inversion problem to be solved is highly ill-conditioned, due to the practical (and economical) impossibility to set up an adequate network for performing classical tomography, therefore a global optimization stochastic technique has been developed to obtain valid results in quasi real time, the implemented multiresolution algorithm is explored. Some significant examples are briefly shown in order to demonstrate the speed, precision and flexibility of the technique. Therefore a significant analysis of the typical algorithm output is presented to show how the problem of recognizing the best solution could be faced.