An Optical Helmet-Tracking System Using EKF-based PF

Abstract

This paper reports on an optical helmet-tracking system that estimates the attitude and position of a pilots head for weapon cueing. The optical helmet-tracking system consists of an infrared stereo camera, infrared LEDs on the helmet, a frame grabber, and a computer for signal processing. In addition, the optical helmet-tracking algorithms have a 3D recursive algorithm, an estimation-and-extraction algorithm, and a 3D motion-estimation algorithm. These algorithms were implemented using image processing, computer vision, and filtering to estimate accurately the head motions of a pilot. In particular, the 3D motionestimation algorithm used an extended Kalman filter (EKF)-based particle filter (PF). It can be used in systems that have non-Gaussian noise distribution with a high-level of accuracy at a high computational speed. We tested the accuracy of the optical helmet-tracking algorithm in estimating 3D head motions.