Skip to Main content Skip to Navigation
Conference papers

Classification in C-band of Doppler signatures of human activities in indoor environment

Pierre Cadart 1 Marin Merlin 1 Giovanni Manfredi 2, 3 Jérémy Fix Chengfang Ren 2, 3 I. Hinostroza 2, 3 Thierry Letertre 2, 3
1 CentraleSupélec
2 SONDRA - Sondra, CentraleSupélec, Université Paris-Saclay
3 SONDRA - Sondra, CentraleSupélec, Université Paris-Saclay (COmUE)
Abstract : This paper explains CentraleSupélec team's approach for the challenge of human activity classification with radar [1]. Our methodology is based on a convolutional network classifier processing the range-time and spectrogram representations. The preprocessing and the neural network architecture presented in this paper allowed us to reach 99% accuracy on challenge's test data of the challenge. A more advanced preprocessing using wavelets is also briefly discussed. Index Terms-Human activity classification, deep convolutional neural networks, spectrogram, Doppler-range diagram, rangetime diagram.
Document type :
Conference papers
Complete list of metadata
https://hal.inria.fr/hal-03022656
Contributor : Fix Jeremy Connect in order to contact the contributor
Submitted on : Tuesday, November 24, 2020 - 9:42:23 PM
Last modification on : Tuesday, December 14, 2021 - 3:01:59 AM

Identifiers

  • HAL Id : hal-03022656, version 1

Collections

CENTRALESUPELEC | SUP_SONDRA | GS-ENGINEERING | HUB-IA

Citation

Pierre Cadart, Marin Merlin, Giovanni Manfredi, Jérémy Fix, Chengfang Ren, et al.. Classification in C-band of Doppler signatures of human activities in indoor environment. IET International Radar Conference 2020, 2021, Chongqing, China. ⟨hal-03022656⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Les métriques sont temporairement indisponibles

 

Contact                    Legal Notice                    Personal Data