Interest in bistatic radar has fluctuated since its first demonstration. Modern multistatic and MIMO radar systems have prompted a resurgence in the field, particularly where imaging radar and automatic target recognition are concerned. The lack of openly-available bistatic imagery and corresponding analysis of the unique artefacts which occur within it is a significant barrier to developing automatic target recognition methods for such systems. This paper looks to address these issues by presenting an appropriate simulation methodology for obtaining bistatic synthetic aperture radar imagery of ground vehicle targets and investigating the features that occur within this imagery. In this paper, a number of effects unique to the bistatic case are presented, and the performance degradation of a classifier at several bistatic angles is empirically demonstrated. A version of the final database will be publicly released to promote wider research into this challenge.