• 通过实测全极化数据分析验证了杂波阐述极化特性

    Through analyzing the real full-polarization data, the polarization characteristic of sea clutter, described before, has been verified.

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  • 实验表明方法应用到全极化sar影像中的道路提取效果好。

    The test indicates that the method is better to been applied in extracting roads in full-polarimetric SAR image.

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  • 极化距离分辨力雷达体制背景下,研究光学雷达目标极化特性

    In this paper, the property of radar target in the optics region is investigated on the basis of polarimetric and high resolution radar system.

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  • 利用日本新泻地区X波段极化数据进行验证,表明方法具有良好的检测性能

    Finally, the performance of this new approach is validated by the X-band full polarimetric SAR data in Niigata area of Japan.

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  • 而后,基于极化分辨雷达,提出利用目标极化信息一维距离像综合识别方法

    Then, a fusion recognition method was proposed using polarized information of target under the high range resolution fully polarized radar.

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  • JPL实验室AIRSAR系统获取L波段旧金山极化SAR数据实验结果验证了该文方法有效性

    The effectiveness of this method is demonstrated using an L-band fully polarimetric SAR image of San Francisco, acquired by the NASA/JPL AIRSAR sensor.

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  • 极化合成孔径雷达SAR图像数据中,提取方位向的地势倾斜度信息,形成极化SAR三维成像

    Terrain slope information may be drawn from polarimetric synthetic aperture radar (SAR) two-dimensional image, so that three-dimensional image can be generated.

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  • 在利用这些参数全极化SAR图像进行处理同时引入图像均衡方法,有效地调节了图像亮度分布情况

    Meanwhile, we bring the method of image balance into SAR image, so the distribution of brightness in the image is renewed.

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  • 理论分析计算机仿真结果均证明极化干扰有效对抗极化滤波技术雷达电子对抗的领域进一步扩展至极化

    Theory analysis and computer-aided simulation prove that full-polarization jamming is effective on polarization filtering. So ECM is extended to polarization domain.

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  • SAR图像的相干影响图像的分类准确度和精度,在进行分类处理双波段全极化SAR图像相干斑进行矢量滤波处理。

    Speckle in SAR images will disturb classification accuracy. Vector filter of speckle is used to dual-frequency images before classification.

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  • SAR图像的相干影响图像的分类准确度和精度,在进行分类处理双波段全极化SAR图像相干斑进行矢量滤波处理。

    Speckle in SAR images will disturb classification accuracy. Vector filter of speckle is used to dual-frequency images before classification.

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