期刊
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
卷 12, 期 11, 页码 4379-4388出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTARS.2019.2949006
关键词
Along-track interferometry (ATI); azimuth offset; convolutional neural network (CNN); ship velocity; synthetic aperture radar (SAR)
类别
资金
- Technology development for Practical Applications of Multi-Satellite data to maritime issues - Ministry of Ocean and Fisheries (MOF, Korea) [20180456-03]
- Disaster-Safety Industry Promotion Program - Ministry of Interior and Safety (MOIS, Korea) [2019-MOIS32-015]
Accurately tracking marine traffic considering security and commercial activities is still challenging despite its increasing global importance. Recently, space-borne synthetic aperture radar (SAR) is being considered to accurately monitor maritime traffic, and techniques to detect the position of ships and estimate their velocity have become essential. Here, we investigated the potential for automatic estimation of ship velocity using the azimuth offset between ships and wakes detected using convolutional neural network (CNN) coupled with SAR imagery. We found that azimuth offset is proportional to the Doppler shift effect of the back-scattered signal in SAR, thus, it relates to the radial velocity of a moving target. Consequently, we propose a method whereby a CNN is applied to automatically detect ship wakes from TanDEM-X data. In this method, ship velocity is calculated using the azimuthal distance (i.e., azimuth offset) between the stern of the detected ship and the vertex of the detected V-shape wake-determined as the intersection of two lines obtained through edge filtering and Radon transforms. The location and number of detected ships are then compared with an automatic identification system (AIS), and the calculated velocity of the ship is compared with the velocity obtained via along-track interferometry and AIS. Results show that our method automatically detects ships and wakes with accuracies of 91.0 and 93.2, respectively, and estimates the velocity of ships with an accuracy of 0.13 ms. This method is effective when wind velocities are not substantially higher than 5.5 ms and ship velocities are not extremely low.
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