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Experimental Validation of Cognitive Radar Anticipation using Stochastic Control

Horne, C; Ritchie, M; Griffiths, H; Hoffmann, F; Charlish, A; (2016) Experimental Validation of Cognitive Radar Anticipation using Stochastic Control. In: Proceedings of the 2016 50th Asilomar Conference on Signals, Systems and Computers. IEEE: Pacific Grove, CA, USA. Green open access

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Abstract

Cognition applied to radar systems is a growing area of research. The majority of cognitive radar research is focused on theory and simulation with little experimental validation. Prior research proposed the application of anticipation within a cognitive radar, demonstrating by simulation that this can provide significant improvements in tracking performance, when compared to non-cognitive radar tracking methods. The approach applied a POMDP algorithm to control the timing of track updates for a target while anticipating the loss of measurements within a known time period/region. This work aims to expand on this concept by using data from a real radar, NetRAD, in order to validate the application of anticipation when tracking a human target.

Type: Proceedings paper
Title: Experimental Validation of Cognitive Radar Anticipation using Stochastic Control
Event: 50th Asilomar Conference on Signals, Systems and Computers
Location: Pacific Grove CA
Dates: 06 November 2016 - 09 November 2016
Open access status: An open access version is available from UCL Discovery
Publisher version: https://www.asilomarsscconf.org/
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Cognitive Radar; Tracking; Anticipation
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10051771
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