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Inverse synthetic aperture radar image focusing using fast adaptive joint time-frequency and three-dimensional motion detection on experimental radar data

机译:利用快速自适应联合时频和三维运动检测对实验雷达数据进行逆合成孔径雷达图像聚焦

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摘要

This study presents two algorithms for enhancing the capabilities of the adaptive joint time-frequency (AJTF) approach and the three-dimensional (3D) motion detection method, respectively, on inverse synthetic aperture radar (ISAR) imaging. The first method is a modified AJTF motion compensation algorithm that is able to employ more than two prominent point scatterers for translation and rotation motion compensation, respectively. The second algorithm enhances a current 3D motion detection method. This algorithm improves the computation time for identifying 3D motion in ISAR images and selects the imaging time intervals with the least 3D motion. With these enhanced detection algorithms, the authors have the ability to distinguish the time intervals when the target undergoes smooth two-dimensional (2D) motion from those containing more chaotic 3D motion. As a result, the authors can reliably detect those time intervals where 2D target motions are predominant to form well-focused ISAR images that are used in automatic target recognition applications.
机译:这项研究提出了两种算法,分别用于增强反联合孔径雷达(ISAR)成像的自适应联合时频(AJTF)方法和三维(3D)运动检测方法的功能。第一种方法是改进的AJTF运动补偿算法,该算法能够采用两个以上的显着点散射体分别进行平移和旋转运动补偿。第二种算法增强了当前的3D运动检测方法。该算法提高了识别ISAR图像中3D运动的计算时间,并选择了3D运动最少的成像时间间隔。利用这些增强的检测算法,作者能够区分目标经历平滑二维(2D)运动的时间间隔与包含更多混沌3D运动的时间间隔。结果,作者可以可靠地检测那些以2D目标运动为主的时间间隔,从而形成用于自动目标识别应用的聚焦良好的ISAR图像。

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  • 来源
    《Signal Processing, IET》 |2010年第4期|p.382-394|共13页
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  • 作者单位

    Defence R&D Canada - Ottawa, Ottawa, Canada;

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  • 正文语种 eng
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