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

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.