Study On High Resolution Processing Algorithm For Sparse Array Microwave Imaging

Microwave imaging technology is an active aerospace and aerial remote sensing method.It has the characteristics of all-day and all-weather work.It has been widely used in environmental protection,disaster monitoring,ocean observation,resource exploration,military reconnaissance,etc.It has become one of the most important tools for resolution earth observation and global resource management.Three-Dimensional Synthetic Aperture Radar Imaging(3D-SAR)is a new type of microwave imaging technology developed on the basis of conventional SAR two-dimensional imaging.3D-SAR imaging technology based on sparse array antenna is one of the important ways to achieve high resolution imaging of 3D-SAR.The sparse array 3D-SAR imaging technology reduces the cost and complexity of the system,effectively suppresses the side lobes of the cross-track direction,and improves The quality of imaging has become one of the hotspots in the field of SAR research in recent years.This paper focuses on array optimization and sparse positive image algorithms.The main research work is as follows:1.The basic principles and steps of the power series polynomial method are introduced.The advantages and limitations of the method are analyzed.The basic principles of compressed sensing and several common methods of compressed sensing are introduced.The advantages and disadvantages of several methods are analyzed.The geometric model and signal model of 3D-SAR imaging are studied.The expression of the transmitted signal is given,and the expression of the echo signal is derived from the expression of the transmitted signal.Then the resolution characteristics of the three dimensions are analyzed in detail.2.Two conventional array antenna down-view 3D-SAR imaging algorithms are studied.Firstly,the 3D RD algorithm is studied.The flow chart of 3D RD algorithm is given.The formula of focusing processing in three dimensions of the algorithm is deduced in detail according to the flow chart.The target simulation is carried out to verify the effectiveness of the algorithm.Then the 3D BP imaging algorithm is studied,the flow chart of the algorithm is given,the idea of the algorithm is introduced briefly,the Doppler phase compensation factor of the algorithm is given,and the effectiveness of the algorithm is verified.A three-dimensional view of the target,a cross-section of each dimension,and a response function are given.3.Developed an array optimization method and a sparse array down-looking 3D-SAR imaging algorithm.In the first case,the antenna array is optimized by the Power Series Polynomial Method.The number of the transmitting array and the receiving array is calculated according to the steps introduced in this Paper,and then verified by the 3D BP algorithm.The results of the antenna array optimization are verified by MATLAB simulation experiments.The result is compared with the simulation result of the full array;Secondly,sparse antenna array down-looking 3D-SAR imaging algorithm based on the compressed sensing,the antenna array is randomly sparse.Based on the conventional antenna array down-looking 3D-SAR imaging algorithm introduced in this paper.The Orthogonal Matching Pursuit Algorithm is used to reconstruct the cross-track data.Algorithm verification using point target simulation experiment.The three-dimensional map of the point target is given,and the two point targets are analyzed in detail.Three dimensions of the two point targets are given.The cross-section and response functions were analyzed and the imaging results were analyzed in detail.