Early Automatic Target Recognizer (ATR) systems have been plagued by inconsistency in frame to frame recognition performance and high false alarm rate. One major source of this variation has been traced to instabilities in the Foward Looking Infrared (FLIR) image. The application of classical segmentation algorithms to the unstable FLIR imagery results in the extraction of a "wobbing" silhouette. This paper explores the attributes of first generation FLIRs that contribute to image instability and artifacts. The value of performing higher samples per dwell in a next generation FLIR sensor is explored along with the benefits of equal sampling in X & Y directions. Image instability and degradation result from a number of different sensor or environment factors that include aliasing due to undersampling, a-c coupling effects, 1/f noise, interface scan effects, mechanical scanner jitter, sensor platform motion, and atmospheric scintillation. To circumvent the sensor effects, the Army CECOM Center for Night Vision & Electro-Optics (C2NVE0) is currently developing an new generation of FLIR sensor under the SAIRS program. In parallel to the sensor development, two next generation ATR system testbeds are being developed under the Multi-Function Target Acquisition Processor (MTAP) program to support the evaluation of next generation ATR technology. These testsbeds include extensive instrumentation and are completely reprogrammable to facilitate the rehosting and evaluation of new ATR techniques. Following the MTAP thrust is a miniaturization program, ALgorithm Adaptive & Diminished DImensioN (ALADDIN), to shrink the size, weight & power of the current ATR processors. This paper presents an overview of the SAIRS, MTAP and ALADDIN programs within the context of the Army's overall plan for FLIR/ATR technology evolution.