Time‐frequency characterisation of bistatic Doppler signature of a wooded area walk at L‐band

Abstract The Doppler signature of a man walking in a forested area analysed at L‐band is presented here. The aim is twofold: to assess the best time‐frequency distribution to characterise the activity; to highlight the similarity of the simulated data to the measured ones to validate the simulation...

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Autores principales:	Giovanni Manfredi, Israel D. Hinostroza Sáenz, Michel Menelle, Stéphane Saillant, Jean‐Philippe Ovarlez, Laetitia Thirion‐Lefevre
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/c1a64117c8fb4d43886829d17c16b7a3
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spelling	oai:doaj.org-article:c1a64117c8fb4d43886829d17c16b7a32021-11-12T15:34:29ZTime‐frequency characterisation of bistatic Doppler signature of a wooded area walk at L‐band1751-87921751-878410.1049/rsn2.12147https://doaj.org/article/c1a64117c8fb4d43886829d17c16b7a32021-12-01T00:00:00Zhttps://doi.org/10.1049/rsn2.12147https://doaj.org/toc/1751-8784https://doaj.org/toc/1751-8792Abstract The Doppler signature of a man walking in a forested area analysed at L‐band is presented here. The aim is twofold: to assess the best time‐frequency distribution to characterise the activity; to highlight the similarity of the simulated data to the measured ones to validate the simulation tool. Indeed, the Doppler‐Time (DT) signal variation represents the main characteristic of Artificial Neural Networks (ANNs) for classification. The more accurately the DT characterises the activity, the higher the machine’s accuracy in classifying it. Besides, in the training data frame, reliable simulated models may supply the amount of data needed by ANN applications. Thus, a short‐time Fourier transform (STFT), a reassigned spectrogram (RE‐Spect), and a pseudo‐Wigner–Ville distribution have been applied to the measured and simulated data. The measurements have been performed using a bistatic radar working at 1 GHz. Then, the measurement setup has been replicated in simulation, and 3‐D human bodies walking in free space have been computed using physical optics. The results show that the STFT is the most suitable time‐frequency method for recognising and classifying the walk. Moreover, the simulated data are in agreement with the measured data, regardless of the chosen Cohen’s technique.Giovanni ManfrediIsrael D. Hinostroza SáenzMichel MenelleStéphane SaillantJean‐Philippe OvarlezLaetitia Thirion‐LefevreWileyarticleTelecommunicationTK5101-6720ENIET Radar, Sonar & Navigation, Vol 15, Iss 12, Pp 1573-1582 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Telecommunication TK5101-6720
spellingShingle	Telecommunication TK5101-6720 Giovanni Manfredi Israel D. Hinostroza Sáenz Michel Menelle Stéphane Saillant Jean‐Philippe Ovarlez Laetitia Thirion‐Lefevre Time‐frequency characterisation of bistatic Doppler signature of a wooded area walk at L‐band
description	Abstract The Doppler signature of a man walking in a forested area analysed at L‐band is presented here. The aim is twofold: to assess the best time‐frequency distribution to characterise the activity; to highlight the similarity of the simulated data to the measured ones to validate the simulation tool. Indeed, the Doppler‐Time (DT) signal variation represents the main characteristic of Artificial Neural Networks (ANNs) for classification. The more accurately the DT characterises the activity, the higher the machine’s accuracy in classifying it. Besides, in the training data frame, reliable simulated models may supply the amount of data needed by ANN applications. Thus, a short‐time Fourier transform (STFT), a reassigned spectrogram (RE‐Spect), and a pseudo‐Wigner–Ville distribution have been applied to the measured and simulated data. The measurements have been performed using a bistatic radar working at 1 GHz. Then, the measurement setup has been replicated in simulation, and 3‐D human bodies walking in free space have been computed using physical optics. The results show that the STFT is the most suitable time‐frequency method for recognising and classifying the walk. Moreover, the simulated data are in agreement with the measured data, regardless of the chosen Cohen’s technique.
format	article
author	Giovanni Manfredi Israel D. Hinostroza Sáenz Michel Menelle Stéphane Saillant Jean‐Philippe Ovarlez Laetitia Thirion‐Lefevre
author_facet	Giovanni Manfredi Israel D. Hinostroza Sáenz Michel Menelle Stéphane Saillant Jean‐Philippe Ovarlez Laetitia Thirion‐Lefevre
author_sort	Giovanni Manfredi
title	Time‐frequency characterisation of bistatic Doppler signature of a wooded area walk at L‐band
title_short	Time‐frequency characterisation of bistatic Doppler signature of a wooded area walk at L‐band
title_full	Time‐frequency characterisation of bistatic Doppler signature of a wooded area walk at L‐band
title_fullStr	Time‐frequency characterisation of bistatic Doppler signature of a wooded area walk at L‐band
title_full_unstemmed	Time‐frequency characterisation of bistatic Doppler signature of a wooded area walk at L‐band
title_sort	time‐frequency characterisation of bistatic doppler signature of a wooded area walk at l‐band
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/c1a64117c8fb4d43886829d17c16b7a3
work_keys_str_mv	AT giovannimanfredi timefrequencycharacterisationofbistaticdopplersignatureofawoodedareawalkatlband AT israeldhinostrozasaenz timefrequencycharacterisationofbistaticdopplersignatureofawoodedareawalkatlband AT michelmenelle timefrequencycharacterisationofbistaticdopplersignatureofawoodedareawalkatlband AT stephanesaillant timefrequencycharacterisationofbistaticdopplersignatureofawoodedareawalkatlband AT jeanphilippeovarlez timefrequencycharacterisationofbistaticdopplersignatureofawoodedareawalkatlband AT laetitiathirionlefevre timefrequencycharacterisationofbistaticdopplersignatureofawoodedareawalkatlband
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Time‐frequency characterisation of bistatic Doppler signature of a wooded area walk at L‐band

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