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Automated ship detection with image enhancement and feature extraction in FMCW marine radars

机译:FMCW船用雷达中具有图像增强功能和特征提取的自动船舶检测

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Automated ship detection process has been an essential need for modern Radar system to perform automatic target tracking. This automated process is more commonly found in pulse radars with high rate of Signal to Noise Ratio (SNR), not in Frequency Modulated Continuous Wave (FMCW) radars with very low rate of SNR. The process of automated ship detection with image enhancement and feature extraction in FMCW radars will be elaborated in this paper. The process of image enhancement is designed to split target from the noise and enhance the image of the target with very low SNR. The output of this process will be classified into several groups by utilizing object geographical, circularity and solidity data. From this process, it clearly shows that with image enhancement, the radar detecting capability in average increases by 390%, 140%, 112% and 62% for radar image within the radii of 2 Nautical Mile (NM), 4 NM, 10 NM and 20 NM. With image classification by geographical data and feature extraction, the ship images will be significantly distinguished from clutter with the accuracy of 90%.
机译:自动化的船舶检测过程一直是现代雷达系统执行自动目标跟踪的必要条件。这种自动化过程更常见于信噪比(SNR)较高的脉冲雷达中,而不是信噪比非常低的调频连续波(FMCW)雷达中。本文将详细介绍FMCW雷达中具有图像增强和特征提取功能的自动舰船检测过程。图像增强过程旨在将目标与噪声分离,并以非常低的SNR增强目标的图像。利用对象地理,圆度和坚固性数据,此过程的输出将分为几类。从这个过程中,可以清楚地看出,通过图像增强,在半径2海里,4海里,10海里的范围内,雷达图像的平均探测能力分别提高了390%,140%,112%和62%。和20海里。通过地理数据对图像进行分类和特征提取,可以将船舶图像与杂波区分开来,准确度达到90%。

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