Objects Classification and Clutter Types Mapping using Polarimetric Radar Detection Algorithms

Yiyang  Song; O. A. Krasnov; A. Yarovoy

doi:10.23919/IRS57608.2023.10172459

Objects Classification and Clutter Types Mapping using Polarimetric Radar Detection Algorithms

Microwave Sensing, Signals & Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

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.

Original language	English
Title of host publication	Proceedings of the 2023 24th International Radar Symposium (IRS)
Publisher	IEEE
Number of pages	10
ISBN (Electronic)	978-3-944976-34-1
ISBN (Print)	978-1-6654-5682-1
DOIs	https://doi.org/10.23919/IRS57608.2023.10172459
Publication status	Published - 2023
Event	2023 24th International Radar Symposium (IRS) - Berlin, Germany Duration: 24 May 2023 → 26 May 2023 Conference number: 24

Publication series

Name	Proceedings International Radar Symposium
Volume	2023-May
ISSN (Print)	2155-5753

Conference

Conference	2023 24th International Radar Symposium (IRS)
Country/Territory	Germany
City	Berlin
Period	24/05/23 → 26/05/23

Bibliographical note

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.

Keywords

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

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10.23919/IRS57608.2023.10172459

Objects_Classification_and_Clutter_Types_Mapping_using_Polarimetric_Radar_Detection_AlgorithmsFinal published version, 6.19 MB

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@inproceedings{0202635b70334e7f887a82252f29cff8,

title = "Objects Classification and Clutter Types Mapping using Polarimetric Radar Detection Algorithms",

abstract = "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{\textquoteright} 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.",

keywords = "Sensitivity, Radar clutter, Signal processing algorithms, Radar detection, Detectors, Gain measurement, Filtering algorithms",

author = "Yiyang Song and Krasnov, {O. A.} and A. Yarovoy",

note = "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.; 2023 24th International Radar Symposium (IRS) ; Conference date: 24-05-2023 Through 26-05-2023",

year = "2023",

doi = "10.23919/IRS57608.2023.10172459",

language = "English",

isbn = "978-1-6654-5682-1",

series = "Proceedings International Radar Symposium",

publisher = "IEEE",

booktitle = "Proceedings of the 2023 24th International Radar Symposium (IRS)",

address = "United States",

}

Song, Y, Krasnov, OA & Yarovoy, A 2023, Objects Classification and Clutter Types Mapping using Polarimetric Radar Detection Algorithms. in Proceedings of the 2023 24th International Radar Symposium (IRS). Proceedings International Radar Symposium, vol. 2023-May, IEEE, 2023 24th International Radar Symposium (IRS), Berlin, Germany, 24/05/23. https://doi.org/10.23919/IRS57608.2023.10172459

Objects Classification and Clutter Types Mapping using Polarimetric Radar Detection Algorithms. / Song, Yiyang ; Krasnov, O. A.; Yarovoy, A.
Proceedings of the 2023 24th International Radar Symposium (IRS). IEEE, 2023. (Proceedings International Radar Symposium; Vol. 2023-May).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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T1 - Objects Classification and Clutter Types Mapping using Polarimetric Radar Detection Algorithms

AU - Song, Yiyang

AU - Krasnov, O. A.

AU - Yarovoy, A.

N1 - Conference code: 24

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - Sensitivity

KW - Radar clutter

KW - Signal processing algorithms

KW - Radar detection

KW - Detectors

KW - Gain measurement

KW - Filtering algorithms

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DO - 10.23919/IRS57608.2023.10172459

M3 - Conference contribution

SN - 978-1-6654-5682-1

T3 - Proceedings International Radar Symposium

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

PB - IEEE

T2 - 2023 24th International Radar Symposium (IRS)

Y2 - 24 May 2023 through 26 May 2023

ER -

Objects Classification and Clutter Types Mapping using Polarimetric Radar Detection Algorithms

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Keywords

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