Image-correlation data association with global uncertainty techniques

A data association technique for target tracking that uses image correlation is enhanced by incorporating uncertainty. The approach uses fuzzy logic to simplify the mapping of the uncertainty to a usable construct to adjust the image generation based on the uncertainty of the measurements. The application of the uncertainty mapping for two methods is developed. The first technique varies the size of the image based on uncertainty. The second modifies the phase variation range that is used to generate the elements in the tile. The techniques are compared to the baseline image correlation technique in a baseline target-tracking example.