Combination of indirect measurements to improve sigmal estimation

Abstract

A form to combine two kinds of indirect measurements to be processed together is proposed for illconditioned problems. Linear individual measurements with unknown proportionality constants jointly considered determine a unique non-linear problem. To solve this problem a method that includes in a single step the recovery of the signal and the calculation of the regularization parameter according to the Generalized Cross Validation technique is proposed. In order to investigate the convenience of simultaneous versus individual processing, a set of synthetic experiments performed on suspensions of polystyrene particles is analyzed. The results clearly show that when the data are jointly processed the quality of the Particle Size Distribution estimated is highly superior. This work shows that simultaneous processing of experimental data from different sources seems to be a valid alternative to improve the quality of indirect measurements.