Super resolution passive radars based on 802.11ax Wi‐Fi signals for human movement detection
Abstract Passive Radars based on Wi‐Fi signals provide an excellent opportunity for human sensing without violating the privacy of individuals. Due to the limited integration time of Wi‐Fi bursts and relatively low bandwidths, Fourier Transform‐based methods do not provide the required accuracy. Her...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-04-01
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| Series: | IET Radar, Sonar & Navigation |
| Online Access: | https://doi.org/10.1049/rsn2.12038 |
| _version_ | 1811261351384842240 |
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| author | Hasan Can Yildirim Jean‐François Determe Laurent Storrer François Rottenberg Philippe De Doncker Jérôme Louveaux François Horlin |
| author_facet | Hasan Can Yildirim Jean‐François Determe Laurent Storrer François Rottenberg Philippe De Doncker Jérôme Louveaux François Horlin |
| author_sort | Hasan Can Yildirim |
| collection | DOAJ |
| description | Abstract Passive Radars based on Wi‐Fi signals provide an excellent opportunity for human sensing without violating the privacy of individuals. Due to the limited integration time of Wi‐Fi bursts and relatively low bandwidths, Fourier Transform‐based methods do not provide the required accuracy. Herein, a Wi‐Fi‐based passive radar algorithm is proposed for indoor human movement detection with super resolution which relies on the ESPRIT algorithm to estimate range/speed parameters from limited number of measurements. To determine the number of targets in the environment, a new Model Order Selection (MOS) method is proposed which exploits the orthogonality between the basis vectors of signal and noise subspaces obtained from the sample covariance matrix of the measurements. The new MOS method along with the proposed algorithm are numerically analysed and compared with other existing methods. Finally, the performance of the algorithm is experimentally validated in indoor conditions. |
| first_indexed | 2024-04-12T19:01:53Z |
| format | Article |
| id | doaj.art-243d33acf34341d4bb08d2aa8677de67 |
| institution | Directory Open Access Journal |
| issn | 1751-8784 1751-8792 |
| language | English |
| last_indexed | 2024-04-12T19:01:53Z |
| publishDate | 2021-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Radar, Sonar & Navigation |
| spelling | doaj.art-243d33acf34341d4bb08d2aa8677de672022-12-22T03:20:07ZengWileyIET Radar, Sonar & Navigation1751-87841751-87922021-04-0115432333910.1049/rsn2.12038Super resolution passive radars based on 802.11ax Wi‐Fi signals for human movement detectionHasan Can Yildirim0Jean‐François Determe1Laurent Storrer2François Rottenberg3Philippe De Doncker4Jérôme Louveaux5François Horlin6OPERA ‐ WCG Université Libre de Brussels Brussels BelgiumOPERA ‐ WCG Université Libre de Brussels Brussels BelgiumOPERA ‐ WCG Université Libre de Brussels Brussels BelgiumOPERA ‐ WCG Université Libre de Brussels Brussels BelgiumOPERA ‐ WCG Université Libre de Brussels Brussels BelgiumICTM ‐ ELEN Université Catholique de Louvain Louvain‐la‐Neuve BelgiumOPERA ‐ WCG Université Libre de Brussels Brussels BelgiumAbstract Passive Radars based on Wi‐Fi signals provide an excellent opportunity for human sensing without violating the privacy of individuals. Due to the limited integration time of Wi‐Fi bursts and relatively low bandwidths, Fourier Transform‐based methods do not provide the required accuracy. Herein, a Wi‐Fi‐based passive radar algorithm is proposed for indoor human movement detection with super resolution which relies on the ESPRIT algorithm to estimate range/speed parameters from limited number of measurements. To determine the number of targets in the environment, a new Model Order Selection (MOS) method is proposed which exploits the orthogonality between the basis vectors of signal and noise subspaces obtained from the sample covariance matrix of the measurements. The new MOS method along with the proposed algorithm are numerically analysed and compared with other existing methods. Finally, the performance of the algorithm is experimentally validated in indoor conditions.https://doi.org/10.1049/rsn2.12038 |
| spellingShingle | Hasan Can Yildirim Jean‐François Determe Laurent Storrer François Rottenberg Philippe De Doncker Jérôme Louveaux François Horlin Super resolution passive radars based on 802.11ax Wi‐Fi signals for human movement detection IET Radar, Sonar & Navigation |
| title | Super resolution passive radars based on 802.11ax Wi‐Fi signals for human movement detection |
| title_full | Super resolution passive radars based on 802.11ax Wi‐Fi signals for human movement detection |
| title_fullStr | Super resolution passive radars based on 802.11ax Wi‐Fi signals for human movement detection |
| title_full_unstemmed | Super resolution passive radars based on 802.11ax Wi‐Fi signals for human movement detection |
| title_short | Super resolution passive radars based on 802.11ax Wi‐Fi signals for human movement detection |
| title_sort | super resolution passive radars based on 802 11ax wi fi signals for human movement detection |
| url | https://doi.org/10.1049/rsn2.12038 |
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