Predictors of Human Efficiency in Radar Detection Tasks
International Conference on Cyber Warfare and Security(2023)
摘要
Aegis operators simultaneously locate and monitor the activity of several hostile targets, intervening and alerting their team when appropriate. Utilizing the Aegis Combat System, operators find, track, and respond to dynamic targets on a radar screen. The demand that operators undergo is often high, inevitably causing strain on cognitive functions and detriments to performance. We applied model-based measures, Cost and Multitasking Throughput, to quantify the influence of external factors on processing efficiency in radar task(s). We captured the influence of three experimental manipulations, each of three levels, on human efficiency to track the location of hostiles and/or detect brief radar interference. We collected participants' performance to complete a multiple object tracking (MOT) task and an electronic attack detection task (EA) using a radar display. A factorial manipulation of conditions comprised changes to task(s) (EA, MOT, or both), the number of targets to track (2, 4, or 6) and the presence or absence of distractors, deemed 'friendlies' (between 500-1000 total tracks). Our novel individual- and model-based approach provided quantitative estimates of human efficiency. We compared the observed variation in efficiency among predictors including target quantity, visual load, and the presence of one or two interrelated tasks. Through quantifying the relationship of these variables to radar detection tasks, we discuss implications of our findings and provide a framework to examine how system designers may develop tools to alleviate observed cognitive demands and/or counter potential threats of electronic attacks in radar detection and tracking tasks.
更多查看译文
关键词
Radar,Electronic warfare,Human efficiency,Dual-tasking
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要