Trajectory measuring of ballistic missile with imaging infrared system based-on knowledge

In order to demonstrate lock-on-after-launch (LOAL) capability, infrared trajectory measuring systems of the future require the ability to autonomously identify and track targets of interest, making use of strong correlation between neighboring-row and non-linear relationship between atmosphere temperature and height analysis etc, a background suppress method based-on knowledge for autonomously acquire and track an extended range target through its entire flight scenario is developed. At the same time we address a method of extracting regions of interest based-on experiential knowledge of detected object. Experiments with real targets show that the method can detect target effectively and reduce false alarm probability and the computational burden of processing the whole image.