Marine target detection using dual-polarimetric SAR imagery

ZHANG Tao; MARINO Armando; NUNZIATA Ferdinando; VELOTTO Domenico; SHAO Weizeng; LI Xiaofeng; MIGLIACCIO Maurizio; XIONG Huilin

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Marine target detection using dual-polarimetric SAR imagery
Marine target detection using dual-polarimetric SAR imagery
2020年24卷第S1期页码：104-109
收稿：2019-10-21，

录用：2020-04-16，

纸质出版：2020-06-07
DOI：
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Marine target detection using dual-polarimetric SAR imagery[J]. 遥感学报, 2020,24(S1):104-109. DOI：

Zhang T,Marino A,Nunziata F,Velotto D,Shao W Z,Li X F,Migliaccio M and Xiong H L. 2020. Marine target detection using dual-polarimetric SAR imagery. Journal of Remote Sensing(Chinese). 24(S1): 104-109 DOI：

摘要

Abstract

In this study

we provide a summary of research advances in the field of maritime target detection using DP (dual-polarimetric) SAR (Synthetic Aperture Radar) imagery

accomplished during the European and China collaboration in the framework of the Dragon-4 program ID 32235. The main innovative contribution is twofold: a) we addressed ship detection proposing an improved GP-PNF (Geometrical Perturbation–Polarimetric Notch Filter)

termed as IGP-PNF

that is characterized by a new feature vector that includes three new scattering features; b) we addressed oil platform detection by contrasting single-polarization SAR methods with polarimetric ones in order to quantify the extra- benefit carried on polarimetric information. The proposed theoretical framework is tested against actual multi-polarization SAR data. In particular

ship detection methods are verified against a Sentinel-1 SAR scene where a large number of ship is present; while

oil platform detection is discussed using TerraSAR-X SAR data. Experimental analysis show that: (1) the IGP-PNF method performs best in terms of clutter-to-target ratio; (2) coherent polarimetric information significantly outperforms single-polarization SAR measurements in highlighting targets in challenging cases.

关键词

Keywords

references

Bueger C . 2015 . What is maritime security? Mar . Policy , 53 : 159 - 164 .

Brusch S , Lehner S , Fritz T , Soccorsi M , Soloviev A and van Schie B . Ship surveillance with TerraSAR-X . IEEE Trans. Geosci. Remote Sens , 49 ( 3 ): 1092 – 1103 .

Zhang T , Yang Z and Xiong H L . PolSAR ship detection based on the polarimetric covariance difference matrix . IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens , 10 ( 7 ): 3348 – 3359 .

Lee J S and Pottier E . 2009 . Polarimetric radar image: from basics to applications. Boca Raton, FL, USA: CRC Press .

Robey F C , Fuhrmann D R , Kelly E J and Nitzberg R . 1992 . A CFAR adaptive matched filter detector. IEEE Trans. Aeros. Electron . Syst. , 28 ( 1 ): 208 – 216 .

Wackerman C C , Friedman K S , Pichel W G , Clemente-Colón P and Li X F . 2001 . Automatic detection of ships in Radarsat-1 SAR imagery. Canadian J . Remote Sens , 27 ( 5 ): 568 – 577 .

Pappas O , Achim A and Bull D . 2018 . Superpixel-level CFAR detectors for ship detection in SAR imagery. IEEE. Geosci. Remote Sens . Letters, Early Access .

Novak L M , Burl M C and Irwing W W . 1993 . Optimal polarimetric processing for enhanced target detection . IEEE Trans. Aerosp. Electron. Syst. , 29 ( 1 ): 234 – 243 .

Chaney R D , Bud M C and Novak L M . 1990 . On the performance of polarimetric target detection algorithms . IEEE Aerosp. Electron. Syst. Mag. , 5 ( 11 ): 10 – 15 .

Sugimoto M , Ouchi K and Nakamura Y . 2013 . On the novel use of model-based decomposition in SAR polarimetry for target detection on the sea . Remote Sens. Lett . 4 ( 9 ): 843 – 852 .

Cloude S R and Pottier E . 1997 . An entropy based classification scheme for land applications of polarimetric SAR . IEEE Trans. Geosci. Remote Sens . 35 ( 1 ): 68 – 78 .

Nunziata F , Migliaccio M and Brown C E . 2012 . Reflection symmetry for polarimetric observation of man-made metallic targets at sea. IEEE J. Ocean . Eng . 37 ( 3 ): 384 – 394 .

Shirvany R , Chabert M and Tourneret J Y . 2013 . Ship and oil-spill detection using the degree of polarization in linear and hybrid/compact

dual-pol SAR . IEEE J . Sel. Top. Appl. Earth Obs. Remote Sens , 5 ( 3 ): 885 – 892 .

Marino A , Cloude S R and Woodhouse I H . 2012 . Detecting depolarized targets using a new geometrical perturbation filter . IEEE Trans. Geosci. Remote Sens . 50 ( 10 ): 3787 – 3799 .

Marino A and Hajnsek I . 2015 . Statistical tests for a ship detector based on the Polarimetric Notch Filter . IEEE Trans. Geosci. Remote Sens . 53 ( 8 ): 4578 – 4595 .

Marino A . 2013 . A notch filter for ship detection with polarimetric SAR data . IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens . 6 ( 3 ): 1219 – 1232 .

Marino A , Sugimoto M , Ouchi K and Hajnsek I . 2014 . Validating a Notch Filter for detection of targets at sea with ALOS-PALSAR Data: Tokyo Bay . IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens . 7 ( 12 ): 4907 – 4918 .

Hannevik T N . 2010 . Polarisation and mode combinations for ship detection using radarsat-2 . In Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS), Honolulu, HI, USA , 3676 – 3679 .

Zhang T , Marino A and Xiong H L . 2018 . A Ship Detector Applying Principal Component Analysis to the Polarimetric Notch Filter . Remote Sens , 10 ( 6 ): 948 .

Tipping M E and Bishop C M . 2002 . Probabilistic principal component analysis. J. R. Stat . Soc . 61 ( 3 ): 611 – 622 .

Marino A , Velotto D and Funziata F . 2017 . Offshore metallic platforms observation using dual-polarimetric TS-X/TD-X satellite imagery: A case study in the Gulf of Mexico . IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens . 10 ( 10 ): 4376 – 4386 .

Cheng L , Yang K , Tong L H , Liu Y X and Li M C . 2013 . Invariant triangle-based stationary oil platform detection from multi-temporal synthetic aperture radar data. J . of Applied Remote Sens . 7 ( 1 ).

Met OfficeUK . Available online: http://www.metoffice.gov.uk/public/weather http://www.metoffice.gov.uk/public/weather .

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