论文标题
ISAR成像的二维无网状超分辨率方法
Two-dimensional gridless super-resolution method for ISAR imaging
论文作者
论文摘要
我们专注于改善反合成孔径雷达（ISAR）成像中移动目标图像的分辨率。这可以通过恢复比其他目标点具有更强反射的目标的散射点来实现，从而增加了目标的雷达横截面（RC）。但是，这些点很少，当收到的数据不完整时，在ISAR图像中，移动目标无法正确识别。为了增加ISAR成像中的分辨率，我们提出了二维重新加权的痕量最小化（2D-RWTM）方法，以在范围和跨范围方向上检索稀疏散射点的频率。该方法是一种无网状的超分辨率方法，它不取决于将散射点拟合到网格上，与其他方法相比，复杂性较小。使用计算机模拟，将提出的2D-RWTM与原子规范最小化（ANM）进行了比较，以平均平方误差（MSE）。结果表明，使用提出的方法，成功恢复了目标的散射点。结果表明，通过选择彼此相邻的不同加权矩阵和散射点，ISAR成像中的恢复仍然成功。
We are focused on improving the resolution of images of moving targets in Inverse Synthetic Aperture Radar (ISAR) imaging. This could be achieved by recovering the scattering points of a target that have stronger reflections than other target points, leading to increasing the higher Radar Cross Section (RCS) of a target. These points, however, are sparse and when the received data is incomplete, moving targets would not be properly recognizable in ISAR images. To increase the resolution in ISAR imaging, we propose the 2-Dimensional Reweighted Trace Minimization (2D-RWTM) method to retrieve frequencies of sparse scattering points in both range and cross-range directions. This method is a gridless super-resolution method, which does not depend on fitting the scattering point on the grids, leading to less complexity compared to the other methods. Using computer simulations, the proposed 2D-RWTM is compared to the Atomic Norm Minimization (ANM) in terms of the Mean Squared Errors (MSE). The results show that using the proposed method, the scattering points of a target are successfully recovered. It is shown that by selecting different weighting matrices and scattering points adjacent to each other, the recovery in ISAR imaging is still successful.
