Krogager decomposition and Pseudo-Zernike moments for polarimetric distributed ATR

Domenico Gaglione; Carmine Clemente; Luca Pallotta; Ian Proudler; Antonio De Maio; John J. Soraghan

Krogager decomposition and Pseudo-Zernike moments for polarimetric distributed ATR

Domenico Gaglione, Carmine Clemente, Luca Pallotta, Ian Proudler, Antonio De Maio, John J. Soraghan

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

15 Citations (Scopus)

Abstract

Automatic Target Recognition (ATR) is one of the most challenging areas of the modern radar signal processing field. In this paper a recognition algorithm for full-polarimetric SAR images, that is robust with respect to rotations and target roll, is presented. It is based on the use of the pseudo-Zernike moments and the Krogager decomposition components, and
exploits multiple sources of information such as polarization and spatial diversity. The effectiveness of the proposed approach has been demonstrated with real full polarimetric SAR data.

Original language	English
Title of host publication	2014 Sensor Signal Processing for Defence (SSPD)
Subtitle of host publication	Conference 2014
Publisher	IEEE
Pages	26-30
Number of pages	5
ISBN (Print)	978-1-4799-5294-6
Publication status	Published - Sept 2014
Event	2014 Sensor Signal Processing for Defence - Scotland, Edinburgh, United Kingdom Duration: 8 Sept 2014 → 9 Sept 2014

Conference

Conference	2014 Sensor Signal Processing for Defence
Country/Territory	United Kingdom
City	Edinburgh
Period	8/09/14 → 9/09/14

Keywords

Krogager
automatic target recognition
spatial diversity
SAR imaging

Cite this

@inproceedings{233df010d41c44b3bb92174bc6bb88ec,

title = "Krogager decomposition and Pseudo-Zernike moments for polarimetric distributed ATR",

abstract = "Automatic Target Recognition (ATR) is one of the most challenging areas of the modern radar signal processing field. In this paper a recognition algorithm for full-polarimetric SAR images, that is robust with respect to rotations and target roll, is presented. It is based on the use of the pseudo-Zernike moments and the Krogager decomposition components, and exploits multiple sources of information such as polarization and spatial diversity. The effectiveness of the proposed approach has been demonstrated with real full polarimetric SAR data.",

keywords = "Krogager, automatic target recognition, spatial diversity, SAR imaging",

author = "Domenico Gaglione and Carmine Clemente and Luca Pallotta and Ian Proudler and \{De Maio\}, Antonio and Soraghan, \{John J.\}",

year = "2014",

month = sep,

language = "English",

isbn = "978-1-4799-5294-6",

pages = "26--30",

booktitle = "2014 Sensor Signal Processing for Defence (SSPD)",

publisher = "IEEE",

note = "2014 Sensor Signal Processing for Defence ; Conference date: 08-09-2014 Through 09-09-2014",

}

TY - GEN

T1 - Krogager decomposition and Pseudo-Zernike moments for polarimetric distributed ATR

AU - Gaglione, Domenico

AU - Clemente, Carmine

AU - Pallotta, Luca

AU - Proudler, Ian

AU - De Maio, Antonio

AU - Soraghan, John J.

PY - 2014/9

Y1 - 2014/9

N2 - Automatic Target Recognition (ATR) is one of the most challenging areas of the modern radar signal processing field. In this paper a recognition algorithm for full-polarimetric SAR images, that is robust with respect to rotations and target roll, is presented. It is based on the use of the pseudo-Zernike moments and the Krogager decomposition components, and exploits multiple sources of information such as polarization and spatial diversity. The effectiveness of the proposed approach has been demonstrated with real full polarimetric SAR data.

AB - Automatic Target Recognition (ATR) is one of the most challenging areas of the modern radar signal processing field. In this paper a recognition algorithm for full-polarimetric SAR images, that is robust with respect to rotations and target roll, is presented. It is based on the use of the pseudo-Zernike moments and the Krogager decomposition components, and exploits multiple sources of information such as polarization and spatial diversity. The effectiveness of the proposed approach has been demonstrated with real full polarimetric SAR data.

KW - Krogager

KW - automatic target recognition

KW - spatial diversity

KW - SAR imaging

UR - http://www.see.ed.ac.uk/drupal/sites/default/files/sspd-conf/SSPD_2014ebook.pdf

M3 - Conference contribution book

SN - 978-1-4799-5294-6

SP - 26

EP - 30

BT - 2014 Sensor Signal Processing for Defence (SSPD)

PB - IEEE

T2 - 2014 Sensor Signal Processing for Defence

Y2 - 8 September 2014 through 9 September 2014

ER -

Krogager decomposition and Pseudo-Zernike moments for polarimetric distributed ATR

Abstract

Conference

Keywords

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