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Selecting Suitable Coherent Processing Time Window Lengths for Ground-Based ISAR Imaging of Cooperative Sea Vessels

机译:选择合适的相干处理时间窗口长度,用于合作海船的地面ISAR成像

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Inverse synthetic aperture radar (ISAR) imaging of sea vessels is a challenging task because their 3-D rotational motion over the coherent processing interval (CPI) often leads to blurred images. The selection of the duration of the CPI, also known as the coherent processing time window length (CPTWL), is critical because it should be short enough to limit the blurring caused by the 3-D rotational motion and long enough to ensure that the desired cross-range resolution is obtained. This paper proposes an algorithm, referred to as the motion-aided CPTWL selector (MACS) algorithm, which selects suitable CPTWLs for ISAR imaging of cooperative sea vessels. The suggested CPTWLs may be used to obtain motion-compensated ISAR images that have the desired medium cross-range resolution and limited blurring due to 3-D rotational motion. The proposed algorithm is applied to measured motion data of three different classes of sea vessels: a yacht, a fishing trawler, and a survey vessel. Results show that longer CPTWLs are needed for larger vessels in order to obtain ISAR images with the desired cross-range resolution. The effectiveness of the CPTWLs, suggested by the MACS algorithm, is shown using measured radar data. The suggested CPTWLs may also be used to select an effective initial CPTWL for Martorella/Berizzi's optimum imaging selection algorithm when it is applied to measured radar data of small vessels. Lastly, the proposed technique offers significant computational savings for radar cross section measurement applications where a few high-quality ISAR images are desired from long radar recordings.
机译:海上逆合成孔径雷达(ISAR)成像是一项艰巨的任务,因为它们在相干处理间隔(CPI)上的3-D旋转运动通常会导致图像模糊。 CPI持续时间的选择(也称为相干处理时间窗口长度(CPTWL))至关重要,因为它的长度应足够短以限制3-D旋转运动引起的模糊,并且长度应足够长以确保所需的获得跨范围分辨率。本文提出了一种称为运动辅助CPTWL选择器(MACS)的算法,该算法选择合适的CPTWL用于合作舰船的ISAR成像。建议的CPTWL可用于获得运动补偿的ISAR图像,这些图像具有所需的介质跨范围分辨率,并且由于3-D旋转运动而具有有限的模糊。所提出的算法适用于三种不同类别的船舶(游艇,渔船和拖船)的测量运动数据。结果表明,较大的血管需要更长的CPTWL,以获得具有所需跨范围分辨率的ISAR图像。使用测得的雷达数据显示了MACS算法建议的CPTWL的有效性。当将建议的CPTWL应用于小型船只的雷达数据时,也可用于为Martorella / Berizzi的最佳成像选择算法选择有效的初始CPTWL。最后,对于需要从长期雷达记录中获取一些高质量ISAR图像的雷达截面测量应用,所提出的技术可节省大量计算量。

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