IR-based ATR systems detect targets based on the heat emanated in the 800-1200 nm range. They offer the clear advantage of being useful at any time, day or night, and can be used in many types of smoke and fog. Most IR-based ATR systems assume that the targets are warmer than the background [ 17 ] (or have characteristic heat signatures w.r.t. the background), and can therefore fail when the target heat, relative to the background, varies unpredictably. This can happen when the engines of a target vehicle have been shut off (possibly making the target as cool as the background), or when objects in the the background (such as rocks on a hot day) are also warm. Figure 1 shows both these situations encountered in a single image from the Ft. Carson data. In this scene, there are two targets; however, only one is clearly visible in the IR image. In addition, part of the background appears almost as bright as the target. Such problems are not uncommon in IR imagery; furthermore, when vehicle structural design is similar, there is no easy way to distinguish between military and civilian vehicles or enemy and friendly vehicles, since they are likely to generate similar IR signatures.
The IR-based ATR system used at the DARPA UGV Demo-C is based on double-window detection [ 11 , 17 ]. Using this method on 25 randomly chosen images from the Ft. Carson IR data set, only 22 out of 50 targets were detected, with 5 false alarms; in addition, the only civilian vehicle in the image set was mistaken for a target. A representative result is shown in figure 1 . While other IR-based techniques have been proposed [ 17 ], there is no strong evidence to indicate that these techniques can overcome the problems inherent to IR data.
Shashi Buluswar