基于SAR图像几何信息挖掘的位姿估计

Yicheng Jiang, Xiaohui Zhao, Yun Zhang, B. Hu, Yuan Zhuang
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引用次数: 5

摘要

位姿归一化有利于提高合成孔径雷达(SAR)自动目标识别的精度。实际上,姿态归一化可以通过根据感兴趣目标的估计姿态旋转给定图像来实现。然而,由于阴影效应导致的SAR图像中的部分缺陷目标影响了姿态估计的精度。提出了一种基于SAR图像中目标几何信息挖掘的姿态估计方法。利用运动和静止目标获取与识别(MSTAR)公开发布数据集对该方法进行了评估。实验结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pose estimation based on exploration of geometrical information in SAR images
Pose normalization is beneficial for improving the accuracy of Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR). In fact, pose normalization can be achieved by rotating the given images according to the estimated pose of the target of interest. However, the partial defect targets in SAR images caused by the shadow effect affects the accuracy of pose estimation. This paper proposes a pose estimation method based on the exploration of the geometrical information of the target of interest in SAR images. The proposed method is evaluated with the moving and stationary target acquisition and recognition (MSTAR) public release dataset. Experimental results verify the effectiveness of the proposed method.
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