Comparison of Detection and Tracking Methods as Applied to OPIR Optics.

摘要

The objective of this research is to investigate and evaluate detection and tracking algorithms suitable for Overhead Persistent InfraRed (OPIR) coverage of moving ground targets. One of the largest hurdles is operating with a low signal-to-noise ratio (SNR) in a cluttered environment. The local contrast method (LCM) and principal component analysis (PCA) detection algorithms will be explored and tested while centroid and correlation tracking algorithms will be discussed. Kalman and alpha-beta filters will be compared and contrasted as viable track prediction techniques. This work will also provide a solid knowledge base for future research on the High Energy Laser (HEL) Beam Control Research Testbed that the Naval Postgraduate School is developing in partnership with Boeing Directed Energy Systems. While they are different applications, both HELs and OPIR share common detection and tracking strategies. Simulation results show that the LCM is superior to PCA. However, the best results are obtained by combining the two. Kalman and alpha-beta filters handle single targets with a constant velocity or acceleration with ease, but advanced tracking methods like the velocity matched filter to provide constraints would provide a more robust solution when performing multiple target tracking.