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Seuring, Stefan |
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Nor Azizi, S. |
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Pato, Margarida Vaz |
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Kölker, Katrin |
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Huber, Oliver |
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Király, Tamás |
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Spengler, Thomas Stefan |
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Al-Ammar, Essam A. |
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Dargahi, Fatemeh |
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Mota, Rui |
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Mazalan, Nurul Aliah Amirah |
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Macharis, Cathy | Brussels |
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Arunasari, Yova Tri |
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Nunez, Alfredo | Delft |
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Bouhorma, Mohammed |
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Bonato, Matteo |
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Fitriani, Ira |
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Autor Correspondente Coelho, Sílvia. |
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Pond, Stephen |
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Okwara, Ukoha Kalu |
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Toufigh, Vahid |
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Campisi, Tiziana | Enna |
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Ermolieva, Tatiana |
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Sánchez-Cambronero, Santos |
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Agzamov, Akhror |
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Krasnov, Oleg A.
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Publications (6/6 displayed)
- 2023An Advanced Data Processing Algorithm for Extraction of Polarimetric Radar Signatures of Moving Automotive Vehicles Using the H/A/α Decomposition Techniquecitations
- 2022Polarimetric Signatures of Moving Automotive Vehicles Based on H/A/α-decomposition
- 2021Auto-calibration of Automotive Radars in Operational Mode Using Simultaneous Localisation and Mappingcitations
- 2015Turbulence intensity estimation using advanced radar methodscitations
- 2015A new model for retrieving information about turbulence intensity from radar signalcitations
- 2006A synergetic radar-lidar technique for the LWC retrieval in water clouds
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document
Polarimetric Signatures of Moving Automotive Vehicles Based on H/A/α-decomposition
Abstract
Polarimetric radar responses from moving automotive targets are studied aiming at target classification using the polarimetric H/A/α-decomposition technique. A signal- and data processing chain has been proposed for the detection and tracking of targets in a multi-target environment in the range-Doppler domain. Polarimetric information of the vehicles is collected during tracking and is analyzed by the H/A/α-decomposition technique. Employing both time averaging and spatial averaging of the statistical coherency matrix, the polarimetric signatures of both vehicles and static clutter have been presented in the two-dimensional H/α-plane. It has been found that the spatial averaging approach results in a polarimetric signature that can be very helpful to distinguish automotive vehicles from static clutter.
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