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<p>This study focused on the development of a human performance model as a baseline performance capability  for automatic change detection software for use in mine warfare. Through a series of survey images, operator  performance was observed under a variety of sonar image conditions, including increasing clutter levels and changes  in image altitude and orientation. While a rough model was developed utilizing only the physical attributes of the  images, to obtain a close fit between the model and actual observations, the variability of personal proficiency was  included in the final model. The inclusion of this parameter greatly improved model accuracy and highlights the need  to better understand differences between operator performances in mine warfare planning.
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<br>Subjects: Mines (Military explosives); Detection; Adaptive control systems; Mathematical models; User-centered system design; Human-machine systems; Computer simulation; Image analysis</div>
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Barrett, Jason S.</div>
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