认知系统工程在空间态势感知决策支持中的应用

IF 2.2 Q3 ENGINEERING, INDUSTRIAL
A. Jaunzemis, K. Feigh, M. Holzinger, D. Minotra, Moses W. Chan
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引用次数: 2

摘要

空间态势感知(SSA)中传感器网络任务的现有方法依赖于20世纪50年代的技术和有限的应用领域,同时也需要大量的人员参与。越来越多的空间物体、传感器和决策需求产生了对收集和融合不同信息的改进方法的需求,以解决有关空间物体环境的假设。这项工作的重点是SSA传感器任务方法中的认知工作。SSA领域认知工作分析的应用突出了该领域固有的能力和约束,这些能力和约束可以推动SSA操作实现决策者目标。还进行了控制任务分析,以导出支持SSA的信息融合和传感器分配任务的认知工作和信息关系的需求。使用派生需求的子集开发了原型决策支持系统。该原型在人在环实验中使用基于假设和基于协方差的调度方法进行了评估。该初步评估的结果表明,操作员有能力使用原型决策支持系统(DSS),使用两种调度方法来解决SSA决策者的假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cognitive Systems Engineering Applied to Decision Support in Space Situational Awareness
Existing approaches for sensor network tasking in space situational awareness (SSA) rely on techniques from the 1950s and limited application areas while also requiring significant human-in-the-loop involvement. Increasing numbers of space objects, sensors, and decision-making needs create a demand for improved methods of gathering and fusing disparate information to resolve hypotheses about the space object environment. This work focuses on the cognitive work in SSA sensor tasking approaches. The application of a cognitive work analysis for the SSA domain highlights capabilities and constraints inherent to the domain that can drive SSA operations toward decision-maker goals. A control task analysis is also conducted to derive requirements for cognitive work and information relationships that support the information fusion and sensor allocation tasks of SSA. A prototype decision-support system is developed using a subset of the derived requirements. This prototype is evaluated in a human-in-the-loop experiment using both a hypothesis-based and covariance-based scheduling approaches. Results from this preliminary evaluation show operator ability to address SSA decision-maker hypotheses using the prototype decision-support system (DSS) using both scheduling approaches.
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来源期刊
CiteScore
4.60
自引率
10.00%
发文量
21
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