Traditional missile warning systems (MWSs) have tended to use the ultra-violet waveband, where the ambient intensity levels tend to be low and the resultant false alarm rate is comparatively small. The development of modern infrared imagers has generated interest in the use of infrared imagers in MWSs. Infrared cameras can detect the heat signatures of missile plumes, which peak in the mid-wave (3-5 micron) infrared band, but they can also contain appreciable levels of noise: including intermittent defects that are of the same size as the potential targets. Typically, both missiles and defects will only occupy a few pixels in each image. This paper reviews a project concerned with developing an MWS algorithm toolbox for use in evaluating infrared MWSs. In particular, the paper discusses some of the main problems associated with detecting and tracking missiles in infrared imagery from a moving platform in the presence of localised image noise.