Classification of Radar Echoes for Identification and Remote Reading of Chipless Millimeter-Wave Sensors

Dominique Henry (1) , Timothée Marchal (1) , Julien Philippe (1) , Patrick Pons (1) , Hervé Aubert (1)

1 LAAS-MINC - Équipe MIcro et Nanosystèmes pour les Communications sans fil

This paper describes the wireless and simultaneous interrogation and identification of multiple passive (zero-power) pressure sensors in an industrial environment with a reading range of at least 4 meters. The 3D beamscanning of the scene is performed from a 24GHz FM-CW radar and for diverse electric field polarizations. The identification is performed using a k-nearest neighbors classification. The benefit of using the cross-polarized electric fields combined with a radar imagery technique is enlightened from the analysis of the background clutter and the simultaneous remote interrogation of several passive pressure sensors at a distance up to 17.7m. The measurement uncertainty on pressure obtained from the proposed long-range wireless technique is finally reported and discussed.

Mots clés: radar imaging; radar polarimetry; target classification; sensor identification; wireless sensor systems

Domaines: Micro et nanotechnologies/Microélectronique; Traitement du signal et de l'image [eess.SP]; Mécanique des structures [physics.class-ph]

Dominique Henry, Timothée Marchal, Julien Philippe, Patrick Pons, Hervé Aubert. Classification of Radar Echoes for Identification and Remote Reading of Chipless Millimeter-Wave Sensors. IEEE Transactions on Microwave Theory and Techniques, 2021, 69 (1), pp.926 - 937. ⟨10.1109/TMTT.2020.3028090⟩. ⟨hal-02969744⟩