In this paper a technique is described for the joint exploitation of several multi-polarimetric SAR images, to the aim of yielding a separate tomographic reconstruction of each of the different Scattering Mechanisms (SM) (such as ground and volume scattering ) that contribute to the received signal. Under large hypotheses it will be shown that the data covariance matrix can be expressed as a Sum of Kronecker Products (SKP), after which it follows that K scattering mechanisms are uniquely identified by K(K-1) real numbers. This result provides the basis to perform SM separation by employing not only model based approaches, generally retained in literature, but also purely algebraic approaches, while yielding the best Least Square solution given the hypothesis of K SMs. Experimental results will be shown basing on airborne data relative to the forest site of Remningstorp, Sweden, acquired by DLR’s ESAR in the framework of the ESA campaign BioSAR2007. Furthermore, it will be shown that the SKP structure also provides a straightforward tool for discussing the well posing of the model inversion problem.