基于随机稀疏分布天线阵列的超分辨微波计算成像分析

    A Study of Super-resolution Microwave Computational Imaging Based on Random Sparsely Distributed Antenna Arrays

    • 摘要: 传统微波成像技术存在天线单元数量多、信号处理复杂、分辨率受限等问题,对此,文中提出了一种基于随机稀疏分布天线阵列的超分辨微波计算成像方法。首先采用稀疏阵列并结合分布式雷达系统的排布方法,在减少天线单元数目的同时实现了与满阵天线相近的成像效果,有效降低了信号处理负担。其次引入随机调制机制,调控天线单元的间距与相位分布,并利用压缩感知理论重构目标图像,显著提升了系统的分辨率。仿真结果表明,文中所提出的随机稀疏分布天线阵列的超分辨性能明显优于传统天线阵列,验证了基于压缩感知理论计算成像方法的可行性和有效性,为微波成像技术的发展提供了新的技术途径。

       

      Abstract: The traditional microwave imaging technology exists the problems of large number of antenna units, complex signal processing and limited resolution, etc. In this regard, a super-resolution microwave computational imaging method based on random sparse distributed antenna array is proposed. Firstly, the sparse array is used and combined with the arrangement method of distributed radar system, which reduces the number of antenna units while realizing the imaging effect similar to that of a full array antenna and effectively reduces the signal processing burden. Secondly, the random modulation mechanism is introduced to regulate the spacing and phase distribution of the antenna units, and the target image is reconstructed by using the theory of compressed perception, which significantly improves the resolution of the system. Simulation results show that the super-resolution performance of the random sparse distribution antenna array proposed in this paper is significantly better than that of the traditional antenna array, which verifies the feasibility and validity of the computational imaging method based on the theory of compressed perception, and provides a new technological path for the development of microwave imaging technology.

       

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