基于全变差正则化的压缩感知毫米波成像方法

毫米波成像技术在人体安检领域有着重要的应用，它采用合成孔径雷达成像原理、宽带信号扫描方式实现三维高分辨率成像。针对其采集空域和频域数据冗余造成的信息和成本浪费问题，提出了在三维毫米波全息成像算法的基础上，采用一种傅里叶操作算子化的频率测量方法，从而实现压缩感知稀疏成像。同时依据成像场景，取图像差分域先验信息，引入了第三维频率维稀疏先验，利用三维全变差L1范数正则化方法将图像重构。实验通过真实回波数据成像效果的展示，证明了拥有高分辨率的三维毫米波图像恢复效果优异，并且与二维全变差正则化方法相比，三维全变差正则化方法重构的图像效果更佳，从而证明了所提方法的有效性。

Compressed Sensing Millimeter Wave Imaging Method Based on Total Variation Regularization

Millimeter wave imaging technology has important applications in the field of human security inspection. It uses synthetic aperture radar imaging principle and broadband signal scanning to achieve three-dimensional high resolution imaging. For the problem of information and cost waste caused by the acquisition of spatial and frequency domain data redundancy, a frequency measurement method based on the Fourier operation operator is proposed based on the three-dimensional millimeter wave holographic imaging algorithm. Thereby achieving compressed sensing sparse imaging. At the same time, according to the imaging scene, the prior information of the image difference domain is taken, and the third-dimensional frequency dimension sparse prior is introduced. The image is reconstructed by the three-dimensional total variation L1 norm regularization method. The experiment demonstrates that the high resolution three-dimensional millimeter wave image recovery effect is excellent through the imaging effect of real echo data. And the image reconstruction effect of the three-dimensional total variation regularization method is better than that of the two-dimensional total variation regularization method. This proves the effectiveness of the proposed method.