Network enabled capability of remote operation: systems engineering and human factors



Davis, John
(2015) Network enabled capability of remote operation: systems engineering and human factors. PhD thesis, University of Liverpool.

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Abstract

Air-to-surface weapons, and the platforms that deliver them, are becoming increasingly automated and remote from operators. The benefits of remotely operated systems have been widely documented, yet the question of accountability remains an issue - both from a legal standpoint and with regards to public opinion. The current focus of the military and industry is to develop weapons with more autonomy and an increased range. This motivation is part of a wider aim for Network Enabled Capability across all military forces. This thesis focuses on one aspect of Network Enabled Capability, the remote re-tasking of air-to-surface weapons in flight. The aim being to explore the potential capabilities of the human operator that may use such a system. Further, this thesis sets out to investigate the differences between using an automated system for re-tasking air-to-surface missiles in flight as opposed to assigning the task to a human operator. A simulation test-bed facility was established to investigate these research aims. The development of this system first required a complete simulation of two air to surface weapon systems, a generic guided bomb, and an extended range missile. These simulation models were integrated into the test-bed facility to allow real-time targeting and firing of the weapon systems in a 3D simulation environment. Two participant trials were carried out to test firstly, the operator terminal designed for task of re-tasking air-to-surface weapons in flight, and secondly, the operator capacity limits when re-tasking multiple air-to-surface weapons against multiple defended targets. These trials found that the system developed was suitable for the task, with interesting results that prove counter to current expectations of operator performance. Further, operator capacity was found to be at a level that can compete with an ideal automated re-tasking system.

Item Type: Thesis (PhD)
Additional Information: Date: 2015-09-19 (completed)
Divisions: Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User: Symplectic Admin
Date Deposited: 16 Aug 2016 10:41
Last Modified: 17 Dec 2022 02:27
DOI: 10.17638/02049959
URI: https://livrepository.liverpool.ac.uk/id/eprint/2049959