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Proceedings Paper

Information processing analysis of human land mine detection skill
Author(s): James J. Staszewski
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Paper Abstract

This paper describes findings from a study conducted to analyze the behavior, knowledge, and thinking that support the highest levels of human land mine detection skill. A recent assessment of land mine detection capability concluded that 'human operators perform better with any detector system than the corresponding fully automated system.' This assessment, plus evidence linking individual differences in detection ability to experience, suggests that methods, data, and theory developed in studying human expertise can be applied to the problems of land mine detection and discrimination. Studies of experts across a variety of skill domains have demonstrated that analyses of experts' skills can yield findings useful for designing efficient and effective training programs and supporting technology development. This initial field study was performed to (a) identify the upper levels of human mine detection capability using currently-fielded hand-held equipment and (b) model the knowledge, thickening, and techniques employed by proficient human operators. Two experienced operators showed sufficiently impressive detection performance to qualify as experts. Data laos show that skilled PSS-12 operator can detect low-metal mines with considerable accuracy. A first-approximation information- processing model of expert operator skill is presented that is based on observation of the operators' activities as they searched for mine targets.

Paper Details

Date Published: 2 August 1999
PDF: 12 pages
Proc. SPIE 3710, Detection and Remediation Technologies for Mines and Minelike Targets IV, (2 August 1999); doi: 10.1117/12.357098
Show Author Affiliations
James J. Staszewski, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 3710:
Detection and Remediation Technologies for Mines and Minelike Targets IV
Abinash C. Dubey; James F. Harvey; J. Thomas Broach; Regina E. Dugan, Editor(s)

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