一种基于数学形态学的SAR船舶检测算法与AIS数据的性能比较

R. Grasso, S. Mirra, A. Baldacci, J. Horstmann, M. Coffin, M. Jarvis
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引用次数: 20

摘要

本文介绍了一种以合成孔径雷达(SAR)真实图像和自动识别系统(AIS)数据为基准的舰船检测算法的性能评估方法。通过利用AIS航迹提供的SAR采集参数和船舶状态信息(速度和航向),校正AIS数据中由SAR引起的位置误差,实现精确的AIS-SAR数据关联。本文在一种基于数学形态学的船舶检测算法上对该方法进行了验证。对在地中海收集的RADARSAT-2数据集进行了评价,其中包括不同获取模式下的图像。给出了检测概率和虚警概率的估计,以及接触位置误差的估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Assessment of a Mathematical Morphology Ship Detection Algorithm for SAR Images through Comparison with AIS Data
This paper describes a procedure to evaluate the performance of ship detection algorithms for Synthetic Aperture Radar (SAR) using real SAR images and Automatic Identification System (AIS) data as ground truth. Accurate AIS-SAR data association is achieved by correcting the AIS data for the SAR induced position errors by exploiting SAR acquisition parameters and vessel state information (speed and course) provided by AIS tracks. The methodology has been tested on a ship detection algorithm based on mathematical morphology which is described in this paper. The evaluation has been carried out on a RADARSAT-2 data set including images at different acquisition modes which was collected in the Mediterranean Sea. Estimates for the detection and the false alarm probability, and the contact position error are provided.
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