Ground Moving Target 2-D Velocity Estimation and Refocusing for Multichannel Maneuvering SAR with Fixed Acceleration
Ground Moving Target 2-D Velocity Estimation and Refocusing for Multichannel Maneuvering SAR with Fixed Acceleration
复制标题
固定加速度多通道机动 SAR 地面移动目标二维速度估计和重聚焦
作者：
Tang Xinxin;Zhang Xiaoling;Shi Jun;Wei Shunjun;Tian Bokun
多通道机动合成孔径雷达（SAR）难以实现地面运动目标的二维速度估计和重聚焦。科普这一问题，提出了一种基于反向投影（BP）和速度合成孔径雷达（VSAR）的新方法。首先利用BP算法重建静态场景，解决多通道机动SAR成像问题。然后，抑制静态杂波，并通过VSAR处理的距离向速度估计。对于方位向速度估计和重聚焦，提出了基于速度辅助BP（VA-BP）和VSAR的速度搜索方法来实现。首先，利用搜索中的每个方位速度和估计的距离速度，通过VA-BP在小尺寸的子图像空间中对运动目标进行成像，即，在图像处理中匹配运动目标的距离历史和多普勒相位。然后，生成多组对应于不同方位速度的多通道SAR子图像，并对每组多通道SAR子图像进行VSAR处理以抑制杂波。在此基础上，利用最小熵准则，在每组多通道SAR子图像中搜索第一个空间接收通道的杂波抑制子图像，获得最佳的重聚焦质量，从而估计出方位向速度。仿真结果表明，该方法对运动目标的二维速度估计和重聚焦具有较高的精度，二维速度估计的绝对误差小于0.1m/s。
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.