| 摘要: |
| 机载聚束合成孔径雷达（Spotlight SAR）是一种SAR的高分辨成像模式。其基本原理是通过对固定区域进行连续观测来实现分米级的高分辨率成像。这种高分辨成像在军事和民用领域中有着极其重要的应用，尤其是在目标判读、解译和识别等方面具有显著优势。然而，随着分辨率的提升，在长时间观测过程中，观测区域内的动目标会产生较长、形态较复杂的散焦和偏移信号。这些信号覆盖在城市建筑物等重要对象上时，会显著降低图像的解释和目标识别的效果。针对上述问题，本文提出了两种动目标干扰抑制方法，第一种方法是通过将相对速度与距离多普勒算法（Range Doppler Algorithm, RDA）相结合，通过迭代调整相对速度参数，使得散焦的动目标能够重新聚焦。在每次迭代中，通过最大幅度指标来检验和判断动目标的重聚焦效果。重聚焦完成后，利用掩膜分离出重聚焦的动目标，再通过逆回波操作恢复出原始的动目标回波信号。最后，通过将原始回波信号减去恢复的动目标回波，即可得到静止场景的回波信号，进而利用距离多普勒算法实现静止场景成像。第二种方法是基于图像序列的动目标干扰抑制方法。该方法通过分割子孔径获得图像序列，在子孔径图像序列中检测并生成掩膜去除散焦动目标信号，进而将处理的图像序列复数据累加生成高分辨静止场景图像。本文采用半物理合成数据进行实验，并通过相关性和相干性运算进行评估，实验结果表明，第一种方法能够有效分离动目标与静止场景回波且效果优于第二种方法。 |
| 关键词: 相对速度 距离多普勒算法 动目标聚焦 回波分离 |
| DOI： |
| 分类号:TN959.73 |
| 基金项目:国家自然科学基金(62131001)；国家自然科学基金(62201011)；国家重点研发青年科学家项目（2023YFB3905200）；市教委科研计划项目（KM202210009004）；北方工业大学配套经费（110051360024XN150-15, 110051360024XN151-08）；北方工业大学毓秀创新项目资助(项目编号2024NCUTYXCX210) |
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| Single-channel Airborne Spotlight SAR Moving Target Interference Suppression Algorithm Based on Relative Velocity |
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林赟, 李洋, 白泽朝, 蒋雯, 赵新亚
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| Abstract: |
| Airborne spotlight synthetic aperture radar ( Spotlight SAR ) is a high resolution imaging mode of SAR. The basic principle is to achieve decimeter-level high-resolution imaging by continuous observation of fixed areas. This high-resolution imaging has extremely important applications in military and civilian fields, especially in target interpretation and recognition. However, with the improvement of resolution, in the long-term observation process, the moving target in the observation area will produce longer and more complex defocus and offset signals. When these signals cover important objects such as urban buildings, the effect of image interpretation and target recognition will be significantly reduced. In view of the above problems, two methods of moving target interference suppression are proposed in this paper. The first method is to combine the relative velocity with the Range Doppler Algorithm ( RDA ), and adjust the relative velocity parameters iteratively so that the defocused moving target can be refocused. In each iteration, the refocusing effect of the moving target is tested and judged by the maximum amplitude index. After the refocusing is completed, the refocused moving target is separated by the mask, and the original moving target echo signal is recovered by the inverse echo operation. Finally, by subtracting the recovered moving target echo from the original echo signal, the echo signal of the static scene can be obtained, and then the range Doppler algorithm is used to realize the imaging of the static scene. The second method is a moving target interference suppression method based on image sequence. The method obtains an image sequence by segmenting the sub-aperture, detects and generates a mask in the sub-aperture image sequence to remove the defocusing moving target signal, and then accumulates the processed image sequence complex data to generate a high-resolution static scene image. In this paper, semi-physical synthetic data are used for experiments, and evaluated by correlation and coherence operations. The experimental results show that the first method can effectively separate the moving target from the static scene echo and the effect is better than the second method. |
| Key words: relative velocity RDA moving target focusing echo separation |