  The recent launch of the Kepler space telescope brings the opportunity to
study oscillations systematically in large numbers of solar-like stars. In the
framework of the asteroFLAG project, we have developed an automated pipeline to
estimate global oscillation parameters, such as the frequency of maximum power
(nu_max) and the large frequency spacing (Delta_nu), for a large number of time
series. We present an effective method based on the autocorrelation function to
find excess power and use a scaling relation to estimate granulation timescales
as initial conditions for background modelling. We derive reliable
uncertainties for nu_max and Delta_nu through extensive simulations. We have
tested the pipeline on about 2000 simulated Kepler stars with magnitudes of
V~7-12 and were able to correctly determine nu_max and Delta_nu for about half
of the sample. For about 20%, the returned large frequency spacing is accurate
enough to determine stellar radii to a 1% precision. We conclude that the
methods presented here are a promising approach to process the large amount of
data expected from Kepler.
