超宽带穿墙雷达偏离网格目标稀疏成像方法

发布时间：2018-01-01 07:22

本文关键词：超宽带穿墙雷达偏离网格目标稀疏成像方法　出处：《仪器仪表学报》2015年04期 　论文类型：期刊论文

【摘要】：在超宽带穿墙雷达成像应用中,由于目标成像空间的稀疏性表示可以采用压缩感知在较少数据采集下获得高分辨、低旁瓣的成像结果。然而,这些稀疏成像方法要求真实目标必须位于预设的网格点上才能保证较好的成像质量,否则会出现严重的虚假目标像。本文提出一种基于修正贝叶斯压缩感知的偏离网格目标稀疏成像方法。该方法对偏离网格目标的感知矩阵在预设网格点进行一阶泰勒级数展开,把真实目标与网格点之间的偏移量视为稀疏贝叶斯模型的参数,然后通过构造的联合概率密度函数利用最大期望方法联合估计目标散射系数和偏移量,保证了目标真实像的准确恢复。仿真和实验结果表明,该方法通过校正目标偏离网格引起的模型误差有效改善了传统稀疏重建方法的成像质量。
[Abstract]:In UWB wall-penetrating radar imaging applications, the sparse representation of target imaging space can obtain high resolution and low sidelobe imaging results with less data acquisition using compression sensing. These sparse imaging methods require that the real target must be located on the preset grid to ensure better imaging quality. Otherwise, serious false target images will appear. In this paper, a sparse imaging method based on modified Bayesian compression perception for deviated grid targets is proposed. This method performs the first order of the perception matrix of the deviated grid target at the preset grid point. Taylor series expansion. The offset between the real target and the grid point is regarded as the parameter of sparse Bayesian model, and then the scattering coefficient and offset of the target are estimated by the maximum expected method through the constructed joint probability density function. The simulation and experimental results show that the proposed method can effectively improve the imaging quality of the traditional sparse reconstruction method by correcting the model error caused by the target deviation from the mesh.
【作者单位】：广西无线宽带通信与信号处理重点实验室;桂林电子科技大学信息与通信学院;
【基金】：国家自然科学基金(61461012) 广西区自然科学基金(2013GXNSFAA019329;2013GXNSFAA 019004) 广西无线宽带通信与信号处理重点实验室项目(GXKL0614106)资助项目
【分类号】：TN957.52
【正文快照】： 1引言超宽带穿墙雷达成像(through-the-wall radar image-ing,TWRI)是一种满足透视建筑物需要的新型技术,包括确定建筑物布局,定位和跟踪室内人员,区分建筑物内人员的活动意图,甚至识别和区分建筑物内感兴趣的静止目标[1-2]。TWRI在执法、火灾救援、应急救助和军事行动等方面

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