This paper presents a novel analytical method measuring the impact of reference model accuracy on tactical, model-based
automatic target acquisition (ATA) algorithm performance. Military tacticians are currently governed by various
standards regarding quality requirements for georeferenced imagery and geospatial data sources. In some new generation
systems, this imagery provides the basis for generating 3D reference models for input into model-based ATA systems.
This paper analyses the criticality of this absolute coordinate accuracy requirement by assessing ATA algorithm
performance using 3D reference models created from a variety of commercially available data sources, including aerial
and terrestrial photography, and airborne laser scanner data. ATA algorithm performance is analysed using a software
tool that uses a variety of open source techniques and image processing functions typically found in tactical, air-to-ground,
model-based ATA systems. Each of the 3D reference models, extracted in a number of different areas of interest,
was matched against a corresponding sequence of infrared video data. This provided a series of results, which were
analysed as a function of both reference model accuracy and object selection and representation. Initial results indicate
that the absolute accuracy of the reference models created for this research has a minor impact on ATA algorithm
performance when compared with the impact of the content of the reference models, taking into account the complexity
of the area of interest. This suggests that a wider array of data sources may be suitable for 3D reference model
construction, than is currently accepted.