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Optimal Time-Frequency Distribution Selection for LPI Radar Pulse Classification

Willetts, B; Ritchie, M; Griffiths, H; (2020) Optimal Time-Frequency Distribution Selection for LPI Radar Pulse Classification. In: Proceedings of the 2020 IEEE International Radar Conference (RADAR). (pp. pp. 327-332). Institute of Electrical and Electronics Engineers (IEEE) Green open access

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Abstract

The work presented in this paper shows the performance of various time-frequency distributions when gathering ELectronic INTelligence (ELINT) from an electromagnetic environment that contains transmissions from radars operating in a Low Probability of Interception (LPI) mode. A radar device varying waveform parameters on a pulse-by-pulse basis to enhance sensing capabilities and/or to avoid interception warrants a method that can assign a unique Pulse Descriptor Word (PDW) to each pulse detected. The simulations presented here makes use of a Deep Learning classifier that is fed by time-frequency representations of noisy LFM and FMCW pulses that each have unique signal parameters. The performance of the radar pulse classifier is conveyed for multiple time-frequency methods. The results show that the time-frequency representation requirements for accurate PDW generation varies for each signal parameter being estimated whilst also having a dependence on the SNR of the intercepted signal.

Type: Proceedings paper
Title: Optimal Time-Frequency Distribution Selection for LPI Radar Pulse Classification
Event: 2020 IEEE International Radar Conference (RADAR)
Location: Washington (DC), USA
Dates: 28th-30th April 2020
ISBN-13: 978-1-7281-6813-5
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/radar42522.2020.9114598
Publisher version: https://doi.org/10.1109/RADAR42522.2020.9114598
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: ELINT, Waveform Classification, Deep Learning, Time-frequency analysis, LPI waveforms
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/10109342
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