Objects Classification and Clutter Types Mapping using Polarimetric Radar Detection Algorithms

Objects Classification and Clutter Types Mapping using Polarimetric Radar Detection Algorithms

Song, Yiyang (Student TU Delft)
Krasnov, O.A. (TU Delft Microwave Sensing, Signals & Systems)
Yarovoy, Alexander (TU Delft Microwave Sensing, Signals & Systems)

2023

Starting from numerical simulation and comparative analysis of different polarimetric detector algorithms using the proposed Gain of Detectability measure, this paper has validated the feasibility and accuracy of polarimetric detectors in scenarios with homogeneous clutter. These algorithms’ application to real radar data with non-homogeneous clutter also shows that detection quality can be seriously improved using detectors that use a priori knowledge of the expected target and clutter polarimetric characteristics. A new application of the Polarimetric Whitening Filter and the Optimal Polarimetric Detector for the classification/mapping of targets and ground-based clutter has been proposed and demonstrated.

Sensitivity
Radar clutter
Signal processing algorithms
Radar detection
Detectors
Gain measurement
Filtering algorithms

http://resolver.tudelft.nl/uuid:0202635b-7033-4e7f-887a-82252f29cff8

https://doi.org/10.23919/IRS57608.2023.10172459

IEEE

2024-01-11

978-1-6654-5682-1

Proceedings of the 2023 24th International Radar Symposium (IRS)

2023 24th International Radar Symposium (IRS), 2023-05-24 → 2023-05-26, Berlin, Germany

Proceedings International Radar Symposium, 2155-5753, 2023-May

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2023 Yiyang Song, O.A. Krasnov, Alexander Yarovoy