The design of an Unattended Ground Sensor (UGS) requires a tradeoff between cost and performance. For designs using a low cost IR microbolometer an array size of 160x120 pixels is a cost effective solution. However, this array size has limited resolving capability. Our goal is to make the best use of the available pixel information from this sensor. There are many reports describing super-resolution (SR) processing as a way to improve image resolution. The definition of SR adopted here is a process where a single high resolution image is created from a sequence of low resolution sub-pixel shifted images. The authors demonstrate the implementation of one SR algorithm from the literature and its benefits to UGS systems using both IR and visible imagery. We describe a software application where the analyst can input a low resolution image frame sequence to produce a high resolution output. The frame sequence can be of a globally shifted frame sequence, a static scene with moving objects or both.