基于随机调制超表面的差分关联成像方法研究

Differential Coincidence Imaging Based on a Randomly Modulated Metamaterial Surface

基于超表面的关联成像系统解决了关联成像系统探测效率低的问题,但其探测模式数量不足导致了其有效成像点数受限。针对这个问题,该文以参考辐射场空间分布1阶统计特征为基础,建立了基于随机调制超表面的关联成像信号模型,分析了成像误差,并与差分关联成像(DCI)方法相结合,给出了具有鲁棒性的基于超表面的关联成像方法,该方法利用不同模式的差分形成了新的探测模式,降低了相关函数的副瓣干扰,从而提升了成像质量。同时,对一种特殊的差分关联成像方法—梯度关联成像(GCI)方法的成像分辨率进行了分析,该方法通过对超表面单元的特殊设计,可以在不获取图像的情况下,直接在成像过程中提取出目标方位向的边缘信息,可以有效提升关联成像系统对目标边缘的提取能力。最后,通过仿真实验验证了该文理论分析的正确性。

The coincidence imaging system based on a metamaterial surface solves the problem of low detection efficiency.Nevertheless,the number of effective imaging points is limited owing to the lack of the detection mode.To solve this problem,based on the first-order statistical characteristics of a reference-radiation field,a correlation-imaging signal model based on a randomly-modulated metamaterial surface is established,and the imaging error is analyzed.This study presents a robust coincidence imaging called Differential Coincidence Imaging(DCI),which uses the differential of different modes to form a new detection mode.The DCI analysis proves that it can improve the imaging quality.At the same time,the resolution of a special DCI method called the Gradient Coincidence Imaging(GCI)method is analyzed,which effectively improves the ability of extracting a target edge.With the special design of a metasurface unit,the edge information of a target can be extracted directly in the imaging process without obtaining an image.Finally,the proposed methods are validated through simulation experiments.