We use cookies to ensure that we give you the best experience on our website. You can change your cookie settings at any time. Otherwise, we'll assume you're OK to continue.

Durham University

Computer Science


Publication details for Professor Toby Breckon

Thomas, P.A., Marshall, G.F., Faulkner, D., Kent, P., Page, S., Islip, S., Oldfield, J., Breckon, T.P., Kundegorski, M.E., Clarke, D. & Styles, T. (2016), Toward Sensor Modular Autonomy for Persistent Land Intelligence Surveillance and Reconnaissance (ISR), in Kolodny, Michael A. & Pham, Tien eds, Proceedings of SPIE 9831: SPIE Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent Intelligence Surveillance and Reconnaissance VII. Baltimore, Maryland, SPIE, Bellingham, WA, 983108.

Author(s) from Durham


Currently, most land Intelligence, Surveillance and Reconnaissance (ISR) assets (e.g. EO/IR cameras) are simply data collectors. Understanding, decision making and sensor control are performed by the human operators, involving high cognitive load. Any automation in the system has traditionally involved bespoke design of centralised systems that are highly specific for the assets/targets/environment under consideration, resulting in complex, non-flexible systems that exhibit poor interoperability. We address a concept of Autonomous Sensor Modules (ASMs) for land ISR, where these modules have the ability to make low-level decisions on their own in order to fulfil a higher-level objective, and plug in, with the minimum of preconfiguration, to a High Level Decision Making Module (HLDMM) through a middleware integration layer. The dual requisites of autonomy and interoperability create challenges around information fusion and asset management in an autonomous hierarchical system, which are addressed in this work. This paper presents the results of a demonstration system, known as Sensing for Asset Protection with Integrated Electronic Networked Technology (SAPIENT), which was shown in realistic base protection scenarios with live sensors and targets. The SAPIENT system performed sensor cueing, intelligent fusion, sensor tasking, target hand-off and compensation for compromised sensors, without human control, and enabled rapid integration of ISR assets at the time of system deployment, rather than at design-time. Potential benefits include rapid interoperability for coalition operations, situation understanding with low operator cognitive burden and autonomous sensor management in heterogenous sensor systems.