Virtual reality and augmented reality environments using helmet-mounted displays create a sense of immersion by closely coupling user head motion to display content. Delays in the presentation of visual information can destroy the sense of presence in the simulation environment when it causes a lag in the display response to user head motion. The effect of display lag can be minimized by predicting head orientation, allowing the system to have sufficient time to counteract the delay. In this paper, anew head orientation prediction technique is proposed that uses a multiple delta quaternion (DQ) extended Kalman filter to track angular head velocity and angular head acceleration. This method is independent of the device used for orientation measurement, relying on quaternion orientation as the only measurement data. A new orientation prediction algorithm is proposed that estimates future head orientation as a function of the current orientation measurement and a predicted change in orientation, using the velocity and acceleration estimates. Extensive experimentation shows that the new method improves head orientation prediction when compared to single filter DQ prediction.

AC electromagnetic trackers are well suited for head tracking but are adversely affected by conductive and ferromagnetic materials. Tracking performance can be improved by mapping the tracking volume to produce coefficients that correct position and orientation (PnO) measurements caused by stationary distorting materials. The mapping process is expensive and time consuming, requiring complicated high-precision equipment to provide registration of the measurements to the source reference frame. In this study, we develop a new approach to mapping that provides registration of mapping measurements without precision equipment. Our method, i.e., the interpolation volume calibration system, uses two simple fixtures, each with multiple sensors in a rigid geometry, to determine sensor PnO in a distorted environment without mechanical measurements or other tracking technologies. We test our method in a distorted tracking environment, constructing a lookup table of the magnetic field that is used as the basis for distortion compensation. The new method compares favorably with the traditional approach providing a significant reduction in cost and effort.