In modern warfare, timely extraction of coordinates from tactical images remains a critical restriction in the targeting loop. Often, a warfighter has immediate access to real time sensor images. However, extracting the true coordinates of a target can be time consuming and difficult. Usually, the sensor will provide basic parameters such as range, heading, and depression angle, which can be used to correlate the image with an on-line database of stereo images. However, these parameters are often in error. This paper documents a research project conducted at the Naval Air Warfare Center, China Lake, California which solves this problem for range and heading values within the Digital Precision Strike Suite correlation and targeting software also developed at this facility. Stereo templates are built using the given range or heading and correlated with the tactical image. Three values from the results of the correlation attempt are fed to a neural network which will determine whether the range or heading is too small or too large. This information is used by a binary search algorithm to adjust the given parameter, perform the correlation again and feed the new values to the neural network. The results obtained are very promising.