An optimal tracking filter for processing sensor data of imprecisely determined origin in surveillance systems

Abstract

This paper develops a new optimal tracking filter that accounts for and minimizes the effects of correlation uncertainties in surveillance systems. This filter reduces to the Kalman filter in the limiting case of no correlation errors and infinite gate sizes, and provides substantially improved performance in environments wherein correlation uncertainties cannot be ignored.