This paper discusses static and dynamic tomographic wave-front (WF) reconstructors tailored to Multi-Object Adaptive Optics (MOAO) for Raven, the first MOAO science and technology demonstrator recently installed on an 8m telescope. We show the results of a new minimum mean- square error (MMSE) solution based on spatio-angular (SA) correlation functions, which extends previous work in Correia et al, JOSA-A 2013 1 to adopt a zonal representation of the wave-front and its associated signals. This solution is outlined for the static reconstruction and then extended for the use of stand-alone temporal prediction and as a prediction model in a pupil plane based Linear Quadratic Gaussian (LQG) algorithm. We have fully tested our algorithms in the lab and compared the results to simulations of the Raven system. These simulations have shown that an increase in limiting magnitude of up to one magnitude can be expected when prediction is implemented and up to two magnitudes when the LQG is used.
