一种两维稀疏的3D-SAR成像方法

A Two-Dimensional Sparse 3D-SAR Imaging Algorithm

  • 摘要: 下视阵列3D-SAR避免了多次飞行带来的去相关问题并且能够很好解决侧视SAR成像存在的阴影、叠掩等问题。但是常规下视阵列3D-SAR跨航向阵元数目较多,增加了系统的成本和复杂度;而且雷达数据需要在三个维度进行采样,回波数据量大。针对以上问题,本文提出了一种跨航向和航迹向两维稀疏的3D-SAR成像算法。在跨航向进行阵列天线随机布局,减少了阵列天线的阵元数目,在航迹向随机稀疏采样,减少了航迹向采样点数。本文采用正交匹配追踪方法对两个维度数据进行稀疏重构。最后,通过点目标仿真实验验证了成像算法的有效性。

     

    Abstract: The down-looking array 3D-SAR avoids the de-correlation problem caused by multiple flights and can well solve the problems of shadow, overlay and the like in side-looking SAR imaging.The number of conventional down-looking array 3D-SAR cross-track array elements is large, which increases the cost and complexity of the system. Moreover, radar data needs to be sampled in three dimensions, and the amount of echo data is large. In view of the above problems, this paper proposes a two-dimensional sparse 3D-SAR imaging algorithm on the cross-track and along-track. The random arrangement of the array antennas in the cross-track reduces the number of array elements of the array antenna, and randomizes the along-track to random sampling, reducing the number of along-track sampling points. In this paper, Orthogonal Matching Pursuit algorithm(OMP) is used to perform sparse reconstruction of two dimensional data. Finally, the effectiveness of the imaging algorithm is verified by point target simulation experiments.

     

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