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Ground Moving Target 2-D Velocity Estimation and Refocusing for Multichannel Maneuvering SAR with Fixed Acceleration

机译:固定加速度的多通道机动SAR地动目标二维速度估计与重聚焦

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摘要

It is difficult for multichannel maneuvering synthetic aperture radar (SAR) to achieve ground moving target 2D velocity estimation and refocusing. In this paper, a novel method based on back projection (BP) and velocity SAR (VSAR) is proposed to cope with the issues. First, the static scene is reconstructed by BP to solve the imaging problem of multichannel maneuvering SAR. Then, the static clutter is suppressed, and the range velocity is estimated via VSAR processing. As for azimuth velocity estimation and refocusing, a velocity search method based on velocity-aided BP (VA-BP) and VSAR is proposed to accomplish them. First, each azimuth velocity in the search and the estimated range velocity are used to image the moving target in a small-sized subimage space by VA-BP, i.e., matching the range history and the Doppler phase of the moving target in the image processing. Then, multiple sets of multichannel SAR subimages corresponding to different azimuth velocities are generated, and the clutter of each set of multichannel SAR subimages is also suppressed by VSAR processing. After that, the azimuth velocity is estimated by searching the clutter-suppressed subimage of the first spatial receiving channel in each set of multichannel SAR subimages with the best refocusing quality measured by the minimum entropy. Simulation results show the proposed method can reach high accuracy in moving target 2D velocity estimation and refocusing with the absolute error of 2D velocity estimation smaller than 0.1 m/s.
机译:多通道机动合成孔径雷达(SAR)很难实现地面移动目标2D速度估计和重新聚焦。针对这一问题,本文提出了一种基于背投影(BP)和速度SAR(VSAR)的新方法。首先,通过BP重建静态场景,以解决多通道机动SAR的成像问题。然后,抑制静态杂波,并通过VSAR处理估算距离速度。对于方位角速度估计和重聚焦,提出了一种基于速度辅助BP(VA-BP)和VSAR的速度搜索方法。首先,将搜索中的每个方位角速度和估计的范围速度用于通过VA-BP在小尺寸子图像空间中对移动目标进行成像,即在图像处理中匹配范围历史和移动目标的多普勒相位。然后,生成对应于不同方位速度的多组多通道SAR子图像,并且通过VSAR处理也抑制了每组多通道SAR子图像的混乱。之后,通过在具有最小熵测得的最佳重聚焦质量的每组多通道SAR子图像中搜索第一空间接收通道的杂波抑制子图像来估计方位速度。仿真结果表明,该方法在运动目标二维速度估计和重新聚焦中具有较高的精度,且二维速度估计的绝对误差小于0.1 m / s。

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