态势感知度量的交互式分析

Derek Overby, J. Wall, J. Keyser
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引用次数: 5

摘要

数字系统用于在各种情况下保持人们的态势感知,包括应急响应、救灾和军事行动。由于这些系统通常在无线环境中运行,并用于支持实时决策,因此所提供的SA数据的准确性对于在新系统的开发中进行测量和评估非常重要。我们的工作是与分析人员一起进行不同系统的评估和性能比较,旨在为军事行动提供高度的态势感知。为此,我们定义了时间和空间度量来衡量每个系统提供的SA数据的准确性。在本文中,我们讨论了建议的SA数据的时间和空间度量,并展示了我们如何在链接协调的多视图环境中提供这些度量,从而使与我们一起工作的分析师能够有效地执行几个关键的分析任务。时间度量的目的是帮助确定网络性能何时对SA数据产生重大影响,从而确定向个体提供不准确位置数据的特定时间段。时间上下文可用于确定任何SA数据不准确的本地或全局性质,然后可使用空间度量来确定对无线系统网络性能的地理影响。我们讨论了度量标准的交互式软件实现,并展示了该分析功能如何使分析人员能够评估在练习过程中观察到的网络延迟和系统性能对SA数据的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interactive analysis of situational awareness metrics
Digital systems are employed to maintain situational awareness of people in various contexts including emergency response, disaster relief, and military operations. Because these systems are often operated in wireless environments and are used to support real-time decision making, the accuracy of the SA data provided is important to measure and evaluate in the development of new systems. Our work has been conducted in conjunction with analysts in the evaluation and performance comparison of different systems designed to provide a high degree of situational awareness in military operations. To this end, we defined temporal and spatial metrics for measuring the accuracy of the SA data provided by each system. In this paper we discuss the proposed temporal and spatial metrics for SA data and show how we provided these metrics in a linked coordinated multiple view environment that enabled the analysts we worked with to effectively perform several critical analysis tasks. The temporal metric is designed to help determine when network performance has a significant effect on SA data, and therefore identify specific time periods in which individuals were provided inaccurate position data for their peers. Temporal context can be used to determine the local or global nature of any SA data inaccuracy, and the spatial metric can then be used to identify geographic effects on network performance of the wireless system. We discuss the interactive software implementation of our metrics and show how this analysis capability enabled the analysts to evaluate the observed effects of network latency and system performance on SA data during an exercise.
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