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Two-Dimensional Ship Velocity Estimation Based on KOMPSAT-5 Synthetic Aperture Radar Data

机译:基于Kompsat-5合成孔径雷达数据的二维船速估计

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摘要

Continuously accumulating information on vessels and their activities in coastal areas of interest is important for maintaining sustainable fisheries resources and coastal ecosystems. The speed, heading, sizes, and activities of vessels in certain seasons and at certain times of day are useful information for sustainable coastal management. This paper presents a two-dimensional vessel velocity estimation method using the KOMPSAT-5 (K5) X-band synthetic aperture radar (SAR) system and Doppler parameter estimation. The estimation accuracy was evaluated by two field campaigns in 2017 and 2018. The minimum size of the vessel and signal-to-clutter ratio (SCR) for optimum estimation were determined to be 20 m and 7.7 dB, respectively. The squared correlation coefficient R2 for vessel speed and heading angle were 0.89 and 0.97, respectively, and the root-mean-square errors of the speed and heading were 1.09 m/s (2.1 knots) and 17.9°, respectively, based on 19 vessels that satisfied the criteria of minimum size of vessel and SCR. Because the K5 SAR is capable of observing a selected coastal region every day by utilizing various modes, it is feasible to accumulate a large quantity of vessel data for coastal sea for eventual use in building a coastal traffic model.
机译:持续累积有关船舶的信息及其在沿海地区的活动,对于维护可持续渔业资源和沿海生态系统来说是重要的。船舶在某些季节和某些时期的船舶的速度,标题,尺寸和活动是可持续沿海管理的有用信息。本文介绍了使用Kompsat-5(K5)X波段合成孔径雷达(SAR)系统和多普勒参数估计的二维血管速度估计方法。 2017年和2018年的两个场运动评估了估计准确性。船舶的最小尺寸和信号到杂波比(SCR)分别测定为20m和7.7dB。用于血管速度和前角度的平方相关系数R2分别为0.89和0.97,并且速度和出头的根平均误差分别基于19艘血管分别为1.09 m / s(2.1结)和17.9°满足血管和SCR的最小尺寸的标准。因为K5 SAR能够通过使用各种模式每天观察所选择的沿海地区,因此可以在建立沿海交通模型中积累大量船只数据来积累大量船只数据。

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