Vishwakarma, Shelly;
Li, Wenda;
Tang, Chong;
Woodbridge, Karl;
Adve, Ravi Raj;
Chetty, Kevin;
(2022)
Attention-enhanced Alexnet for improved radar micro-Doppler signature classification.
IET Radar, Sonar & Navigation
10.1049/rsn2.12369.
(In press).
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Abstract
This work introduces an attention mechanism that can be integrated into any standard convolution neural network to improve model sensitivity and prediction accuracy with minimal computational overhead. The attention mechanism is introduced in a lightweight network – Alexnet and its classification performance for human micro-Doppler signatures is evaluated. The Alexnet model trained with an attention module can implicitly highlight the salient regions in the radar signatures while suppressing the irrelevant background regions and consistently improving network predictions. Network visualizations are provided through class activation mapping, providing better insights into how the predictions are made. The visualizations demonstrate how the attention mechanism focusses on the region of interest in the radar signatures.
| Type: | Article |
|---|---|
| Title: | Attention-enhanced Alexnet for improved radar micro-Doppler signature classification |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1049/rsn2.12369 |
| Publisher version: | https://doi.org/10.1049/rsn2.12369 |
| Language: | English |
| Additional information: | Copyright © 2022 The Authors. IET Radar, Sonar & Navigation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
| Keywords: | image classification, micro Doppler, radar target recognition |
| 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 Security and Crime Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10162251 |
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