Analysis of ship wake features and extraction of ship motion parameters from SAR images in the Yellow Sea

Abstract

The identifying features of ship wakes in synthetic aperture radar (SAR) remote sensing images are of great importance for detecting ships and for extracting ship motion parameters. A statistical analysis was conducted on the identifying features of ship wakes in SAR images in the Yellow Sea. In this study, 1091 ship wake sub-images were selected from 327 SAR images in the Yellow Sea near Qingdao. Analysis of the identifying features of ship wakes in SAR images revealed that both turbulent wakes and Kelvin wakes account for the majority of ship wakes, with turbulent wakes occurring approximately four times as frequently as Kelvin wakes. Narrow-V wakes and internal wave wakes were comparatively rare, which is due to the peculiarities of the radar system parameters and marine environments required to observe these wakes. Additionally, we extracted ship motion parameters from four types of ship wakes in the SAR images. Specifically, internal wave wakes in SAR images in the Yellow Sea were also used to extract ship motion parameters. Validation of the extracted parameters indicated that the extraction of these parameters from ship wakes is a viable and accurate approach for the acquisition of ship motion parameters. These results provide a solid foundation for the commercialization of SAR-based technologies for detecting ships and extracting ship motion parameters.

Keywords

synthetic aperture radar / remote sensing / ship wake / ship motion parameter

References

[1] Ai J Q, Qi X Y, Yu W, Liu F (2010). A new ship wake CFAR detection algorithm in SAR images based on image segmentation and normalized Hough transform. Journal of Electronic & Information Technology, 32(11): 2668–2673

[2] An Q, Pan Z, You H (2018). Ship detection in Gaofen-3 SAR images based on sea clutter distribution analysis and deep convolutional neural network. Sensors (Basel), 18(2): 334

[3] Arnold-Bos A, Martin A, Khenchaf A (2007). Obtaining a ship’s speed and direction from its Kelvin wake spectrum using stochastic matched filtering.  Proc Int Geosci Remote Sens Symp, 1106–1109

[4] Biondi F (2018). Low-rank plus sparse decomposition and localized radon transform for ship-wake detection in synthetic aperture radar images. IEEE Geosci Remote Sens Lett, doi: 10.1109/LGRS. 2018.2868365

[5] Fan K G, Fu B, Gu Y, Yu X, Liu T, Shi A, Xu K, Gan X (2015). Internal wave parameters retrieval from space-borne SAR image. Front Earth Sci, 9(4): 700–708

[6] Graziano M D, D’Errico M, Rufino G (2016). Ship heading and velocity analysis by wake detection in SAR images. Acta Astronaut, 128: 72–82

[7] Hennings I, Romeiser R, Alpers W, Viola A (1999). Radar imaging of Kelvin arms of ship wakes. Int J Remote Sens, 20(13): 2519–2543

[8] Hogan G G, Chapman R D, Watson G, Thompson D R (1994). Observations of ship-generated internal waves in SAR images from Loch Linnhe, Scotland, and comparison with theory and in situ internal wave measurements. IEEE Trans Geosci Remote Sens, 34(2): 1363–1369

[9] Jackson C R, Apel J R (2004). Synthetic Aperture Radar Marine User’s Manual. National Oceanic and Atmospheric Administration

[10] Lyden J D, Hammond R R, Lyzenga D R, Shuchman R A (1988). Synthetic aperture radar imaging of surface ship wakes. Journal of Geophysical Research, 1988, 193: 12293–12300

[11] Melsheimer C, Lim H, Shen C M (1999). Observation and analysis of ship wakes in ERS-SAR and SPOT image. Proceedings of the 20th Asian Conference on Remote Sensing, 22–25

[12] Munk W H (1987). Ship from space. Proceedings of the Royal Society London, A (412): 231–254

[13] Ouchi K (2013). Recent trend and advance of synthetic aperture radar with selected topics. Remote Sensing, 5: 716–807

[14] Ouchi K, Stapleton N R, Barber B C (1997). Multi-frequency SAR images of ship-generated internal waves. Int J Remote Sens, 18(18): 3709–3718

[15] Oumansour K, Wang Y, Saillard J (1994). Application of polarimetric synthetic aperture radar to a ship wake in simulation. Symposium on Antenna Technology and Applied Electromagnetics, Ottawa, Canada, 661–664

[16] Panico A, Graziano M D, Renga A (2017). SAR-based vessel velocity estimation from partially imaged Kelvin pattern. IEEE Geosci Remote Sens Lett, 14(11): 2067–2071

[17] Skoelv A, Wahl T, Eriksen S (1988). Simulation of SAR imaging of ship wakes. Proceedings of IGARSS’88 Symposium, 13–16

[18] Stapleton N R (1997). Ship wakes in radar imagery. Int J Remote Sens, 18(6): 1381–1386

[19] Sun Y, Liu P, Jin Y Q (2018). Ship wake components: isolation, reconstruction, and characteristics analysis in spectral, spatial, and TerraSAR-X image domains. IEEE Trans Geosci Remote Sens, 56(7): 4209–4224

[20] Swanson C V (1984). Radar Observability of Ship Wakes. Report of Cortana Corporation

[21] Tings B, Velotto D (2018). Comparison of ship wake detectability on C-band and X-band SAR. Int J Remote Sens, 39(13): 4451–4468

[22] Vesecky J F, Stewart R H (1982). The observation of ocean surface phenomena using imagery from the Seasat synthetic aperture radar: an assessment. J Geophys Res, 87(C5): 3397–3430

[23] Wang L L, Chen H X (2009). Multi-ship wakes detection method based on recursive modified Hough transform field. J Syst Eng Electron, 31(4): 834–837

[24] Xu Z, Tang B, Cheng S (2018). Faint ship wake detection in PolSAR images. IEEE Geoscience & Remote Sensing Letters, 2018, 15(7): 1055–1059

[25] Zilman G, Miloh T (1997). Radar backscatter of a V-like ship wake from a sea surface covered by surfactants. Twenty-first Symposium on Naval hydrodynamics

[26] Zilman G, Zapolski A, Marom M (2004). The speed and beam of a ship from its wake’s SAR images. IEEE Trans Geosci Remote Sens, 42(10): 2335–2343

[27] Zilman G, Zapolski A, Marom M (2015). On detectability of a ship’s Kelvin wake in simulated SAR images of rough sea surface. IEEE Trans Geosci Remote Sens, 53(2): 609–619

Acknowledgments

This work is jointly funded by the Shandong Natural Science Foundation (Grant No. ZR2017LD014), the National Natural Science Foundation of China (Grant Nos. 41476088, 41876208, and 41576174), the National Key Projects for Marine Environmental Security (Grant No. 2016YFC1403201) and the National High Resolution Project of China (Grant No. 41Y30B12-9001-14/16). We also appreciate Mrs. Aiqin SHI from State Key Laboratory of Satellite Ocean Environment Dynamics (SOED) of Second Institute of Oceanography for her kindly processing the remote sensing images.

RIGHTS & PERMISSIONS

2019 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature