  Cross-matching catalogues from radio surveys to catalogues of sources at
other wavelengths is extremely hard, because radio sources are often extended,
often consist of several spatially separated components, and often no radio
component is coincident with the optical/infrared host galaxy. Traditionally,
the cross-matching is done by eye, but this does not scale to the millions of
radio sources expected from the next generation of radio surveys. We present an
innovative automated procedure, using Bayesian hypothesis testing, that models
trial radio-source morphologies with putative positions of the host galaxy.
This new algorithm differs from an earlier version by allowing more complex
radio source morphologies, and performing a simultaneous fit over a large
field. We show that this technique performs well in an unsupervised mode.
