eprintid: 10078510
rev_number: 20
eprint_status: archive
userid: 608
dir: disk0/10/07/85/10
datestamp: 2019-07-23 13:21:06
lastmod: 2021-09-26 22:52:15
status_changed: 2019-11-22 14:26:37
type: article
metadata_visibility: show
creators_name: Patel, JS
creators_name: Fioranelli, F
creators_name: Ritchie, M
creators_name: Griffiths, HD
title: Fusion of Deep Representations in Multistatic Radar Networks to Counteract the Presence of Synthetic Jamming
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F46
keywords: Radar; Multistatic Radar; Human Micro
Doppler; Radar Classification; Fusion; DNN; Synthetic Jamming
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: Micro-Doppler signatures are extremely valuable in
the classification of a wide range of targets. This work
investigates the effects of jamming on micro-Doppler
classification performance and explores a potential deep topology
enabling low bandwidth data fusion between nodes in a
multistatic radar network. The topology is based on an array of
three independent deep neural networks (DNNs) functioning
cooperatively to achieve joint classification. In addition to this, a
further DNN is trained to detect the presence of jamming and
from this it attempts to remedy the degradation effects in the
data fusion process. This is applied to real experimental data
gathered with the multistatic radar system NetRAD, of a human
operating with seven combinations of holding a rifle-like object
and a heavy backpack which is slung on their shoulders. The
resilience of the proposed network is tested by applying synthetic
jamming signals into specific radar nodes and observing the
networks’ ability to respond to these undesired effects. The
results of this are compared with a traditional voting system
topology, serving as a convenient baseline for this work.
date: 2019-08-01
date_type: published
official_url: https://doi.org/10.1109/JSEN.2019.2909685
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1673681
doi: 10.1109/JSEN.2019.2909685
lyricists_name: Griffiths, Hugh
lyricists_name: Ritchie, Matthew
lyricists_id: HDGRI98
lyricists_id: MARIT18
actors_name: Ritchie, Matthew
actors_id: MARIT18
actors_role: owner
full_text_status: public
publication: IEEE Sensors Journal
volume: 19
number: 15
pagerange: 6362-6370
citation:        Patel, JS;    Fioranelli, F;    Ritchie, M;    Griffiths, HD;      (2019)    Fusion of Deep Representations in Multistatic Radar Networks to Counteract the Presence of Synthetic Jamming.                   IEEE Sensors Journal , 19  (15)   pp. 6362-6370.    10.1109/JSEN.2019.2909685 <https://doi.org/10.1109/JSEN.2019.2909685>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10078510/1/Fusion%20of%20Deep%20Representations%20in%20a%20Multistatic%20Radar%20Network%20to%20Counteract%20the%20Presence%20of%20Synthetic%20Jamming_R1.pdf