3D Radar Imaging Based on Target Scenario Structer Sparse Reconstruction
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摘要: 基于成像场景散射强度稀疏表示的3维雷达成像结果对目标的外形几何细节体现较差，不利于目标识别。该文首先分析了目标在成像场景内散射强度的结构化特征，然后以散射点梯度信息进行了结构化稀疏表示，构建了基于目标散射强度梯度变化的结构化稀疏重构模型，最后通过改进的联合正交匹配追踪算法重构出目标3维图像。实验结果表明，该方法具有较好的抗噪性能和成像质量，可以更好地反映目标外形几何特征。Abstract: The three-Dimensional (3D) radar imaging mathods based on sparse representation by the scattering intensity of imaging sceen has a poor representation of geometric details on the shape of the target, which isn’t conducive to target recognition. Firstly, the structural characteristics of scattering intensity in the imaging scenario are analyzed in this paper. Then, by the structured sparse representation with the gradient information of scattering points, a structured sparse reconstruction model is constructed. Finally, the 3D imaging result is reconstructed by a improved joint Orthogonal Matching Pursuit (OMP) algorithm. The experimental results show that the proposed method has good anti-noise and imaging quality, and can reflect the geometric details of the target.
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表 1 算法性能对比
OMP 正则化${\ell _1}$ 本文所提方法 迭代次数 12 120 74 距离分辨率(m) 0.162 0.158 0.164 方位/高度分辨率(m) 0.142 0.140 0.146 MSE 2.87e-4 8.36e-5 4.76e-6 SSIM 0.673 0.831 0.912 
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