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首页> 外文会议>International symposium on multispectral image processing and pattern recognition >A Modified Sparse Reconstruction Method for Three-Dimensional Synthetic Aperture Radar Image
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A Modified Sparse Reconstruction Method for Three-Dimensional Synthetic Aperture Radar Image

机译：三维合成孔径雷达图像的一种改进的稀疏重建方法

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There is an increasing interest in three-dimensional Synthetic Aperture Radar (3-D SAR) imaging from observed sparse scattering data. However, the existing 3-D sparse imaging method requires large computing times and storage capacity. In this paper, we propose a modified method for the sparse 3-D SAR imaging. The method processes the collection of noisy SAR measurements, usually collected over nonlinear flight paths, and outputs 3-D SAR imagery. Firstly, the 3-D sparse reconstruction problem is transformed into a series of 2-D slices reconstruction problem by range compression. Then the slices are reconstructed by the modified SLO (smoothed l_0 norm) reconstruction algorithm. The improved algorithm uses hyperbolic tangent function instead of the Gaussian function to approximate the l_0 norm and uses the Newton direction instead of the steepest descent direction, which can speed up the convergence rate of the SL0 algorithm. Finally, numerical simulation results are given to demonstrate the effectiveness of the proposed algorithm. It is shown that our method, compared with existing 3-D sparse imaging method, performs better in reconstruction quality and the reconstruction time.
机译：从稀疏散射数据中获取三维合成孔径雷达（3-D SAR）图像的兴趣日益浓厚。然而，现有的3-D稀疏成像方法需要大量的计算时间和存储容量。在本文中，我们提出了一种改进的稀疏3-D SAR成像方法。该方法处理通常在非线性飞行路径上收集的嘈杂SAR测量值，并输出3-D SAR图像。首先，通过距离压缩将3D稀疏重建问题转化为一系列2D切片重建问题。然后，通过改进的SLO（平滑的l_0范数）重建算法来重建切片。改进后的算法使用双曲正切函数代替高斯函数逼近l_0范数，并使用牛顿方向代替最陡下降方向，从而可以加快SL0算法的收敛速度。最后，数值仿真结果证明了该算法的有效性。结果表明，与现有的3D稀疏成像方法相比，我们的方法在重建质量和重建时间方面表现更好。

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