A Cognitive Analysis of Leveraging LADAR to Support Combat Identification
ABSTRACT: Imagery analysts must frequently identify targets in rapidly changing environments where mistakes can have tragic consequences. LADAR is an emerging sensor technology that provides a rich data source for human analysts in support of combat identification. However, the primary focus of prior research has been on developing LADAR as a technology without adequately considering how an analyst will exploit LADAR data. Additionally, providing 3D LADAR data to an analyst when they are already trying to manage ever-increasing amounts of data in multiple forms can promote data overload. Further, issues of trust in automation must be examined. We will leverage innovative research methodologies and cognitive task analyses to identify the cognitive demands and challenges of combat identification analysts and determine how 3D LADAR data can address these gaps. We will develop visualization concepts based on ecological interface design principles to support 3D data exploitation. This effort will utilize a decision-centered design approach to develop a truly collaborative system that will allow a human analyst and assisted target recognition systems to work together to exploit 3D LADAR data. These concepts will generalize to other domains where the exploitation of 3D data is critical including medical imagery, border surveillance, and airport screening. BENEFIT: Within the military, this research will have direct applicability to military intelligence and any analysts who are responsible for exploiting 3D LADAR data for combat identification. The proposed system will provide innovative visualization concepts that will allow analysts to interpret and act on 3D data. This ability has direct relevance to any government or private sector group that uses 3D data, including DHS (border surveillance and airport screening) and the medical community (diagnosis using 3D imaging).
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