Warfighter-in-the-loop: mental models in airborne minefield detection

Abstract

The warfighter analyst in the data processing ground control station plays an integral role in airborne minefield detection system. This warfighter-in-the-loop (WIL) is expected to reduce the minefield false alarm rate by a factor of 5. In order to achieve such a significant false alarm reduction and to facilitate the development of an efficient WIL interface, it is critical to evaluate different aspects of WIL operations for airborne minefield detection. Recently, researchers at the University of Missouri -Rolla have developed a graphical user interface (HILMFgui) application using MATLAB to evaluate minefield detection performance for the operator. We conducted a series of controlled experiments with HILMFgui using ten participants. In these experiments, we video-recorded all the experiments and conducted post-experiment interviews to learn more about the usability of the interface and the cognitive processes involved in minefield detection. The effect of various factors including the availability of automatic target recognition (ATR), availability of zoom and time constraints were considered to evaluate their influence on operator performance. Qualitative results of the factors affecting the warfighter performance in the minefield detection loop are discussed. Through the qualitative data analysis, we observed two different types of participants (classified here as aggressive and cautious). We also identified three primary types of mental models: mine centric, mine-field centric, and logical placement. Those who used a primarily mine focus had a substantially higher false alarm rate than those whose mental models were more consistent with a mine-field centric or logical placement perspective.