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.
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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.
| Type: | Article |
|---|---|
| Title: | Fusion of Deep Representations in Multistatic Radar Networks to Counteract the Presence of Synthetic Jamming |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/JSEN.2019.2909685 |
| Publisher version: | https://doi.org/10.1109/JSEN.2019.2909685 |
| 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: | Radar; Multistatic Radar; Human Micro Doppler; Radar Classification; Fusion; DNN; Synthetic Jamming |
| UCL classification: | UCL 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/10078510 |
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