Automatic Target Recognition in SAR imagery becomes popular in recent years. The typical Automatic Target Recognition system consists of three stages: detection

discrimination and classification. Detection

whose role is to find regions in SAR imagery that contains potential targets

will inevitably produce false alarms. The false alarms are then further reduced by the following stage

discrimination. These two stages together are called prescreening

which are very important in the whole ATR system. If they act highly efficient

i.e.

they can reject almost all the background clutter

the computational cost in the process of classification will be greatly reduced. At present

there are three methods in the field of automatic target detection: CFAR

multi-resolution model

detection methods based on image phases. There are also quite a few methods for target discrimination. In this paper we present an overview on the algorithms and their results for automatic target detection and discrimination in SAR imagery. The research trends of these fields are also given at the end of the paper.