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Cognitive Engineering in Algorithm Development for Multisensor Data Fusion in Military Applications

机译:军事应用中多传感器数据融合算法开发中的认知工程

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摘要

In battlefield situations, human operators are bombarded with substantial amounts of information and expected to make near-instantaneous decisions. The large amounts of information, coupled with short decision times and the need to reduce the potential of making incorrect decisions, create the possibility for information overload. This problem is especially prominent in military applications involving imagery from multiple sensors. Computer-based algorithms for fusing pertinent sets of imagery have proven somewhat useful for alleviating this problem. However, little research has been done on designing multisensor data fusion systems using principles of cognitive engineering, which involves the consideration of human cognition during the design process. The design of a sensor fusion system using principles from cognitive engineering would create a more natural relationship between human and machine, and would thus be extremely effective in reducing operator error in military situations. This paper explores the need for integrating human reasoning and cognition in algorithm development for multisensor fusion applications.
机译:在战场上,操作员会受到大量信息的轰炸,并有望做出近乎瞬时的决定。大量的信息,加上较短的决策时间以及减少做出错误决策的可能性的需求,造成了信息过载的可能性。在涉及来自多个传感器的图像的军事应用中,这个问题尤为突出。事实证明,用于融合相关图像集的基于计算机的算法在缓解此问题方面有些有用。但是,关于使用认知工程原理设计多传感器数据融合系统的研究很少,这涉及在设计过程中考虑人类认知的问题。使用来自认知工程原理的传感器融合系统的设计将在人与机器之间建立更自然的关系,因此在减少军事情况下的操作员错误方面非常有效。本文探讨了在多传感器融合应用程序的算法开发中整合人类推理和认知的需求。

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