Date of Award
12-1994
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Electrical and Computer Engineering
First Advisor
Patricia Lawlis, PhD
Abstract
Software engineering tools and techniques were applied to design and implement an application that reduces lag typically present in virtual environment displays. The application was a Multiple Model Adaptive Estimator (MMAE), composed of three Kalman filters, that predicted head orientation one sample period into the future. The environment rendering software used these predictions to generate the environment display. Each of the filters in the MMAE was designed for a different assumed head motion type (benign, moderate, or heavy), which allowed the MMAE to adapt to changes in head movement characteristics. The use of Ada 9X as an implementation language for a virtual environment applications was also investigated. Ada 9X provides object-oriented features for design and development, and it also offers software engineering support that makes it preferable to C or C++ for the application developed. Two significant results were produced. The first is a performance baseline for the MMAE that can be used as a benchmark for future research in this area. The other is a performance-based comparison of equivalent Ada 9X and C++ graphics applications in which Ada 9X performance was practically identical to C++. This second result is somewhat surprising, and should be investigated further.
AFIT Designator
AFIT-GCS-ENG-94D-21
DTIC Accession Number
ADA289299
Recommended Citation
Russell, James E., "Multiple Model Adaptive Estimation and Head Motion Tracking in a Virtual Environment: An Engineering Approach" (1994). Theses and Dissertations. 6393.
https://scholar.afit.edu/etd/6393
Comments
The author's Vita page is omitted.