Research On Tomography SAR Imaging Method Based On Compression Sensing

The three-dimensional technology of Synthetic Aperture Radar(SAR)has not only retained the advantage of traditional SAR system,such as all-weather,all-time and so on,but also avoided the fuzzy problem which coming from the shadow of tthree-dimensional imaging to the two-dimensional imaging.It can completely separate the height of a target from the range direction of a target,and has widly application prospect such as the field of terrain mapping,military reconnaissance,Accuratly evaluating disaster and dynamic monitoring of deep forest resources and ecological monitoring,so it is an important hot research of radar science researcher.Because of it does does not need to deliberately control the flight trajectory,requires a specific position control,3-D images of Tomographic SAR utilizes the same area of a SAR 2D image,which uses synthesize aperture principle again in the vertical direction,and it is turly achieving high-resolution three-dimensional imaging,which has a great application prospects in the radar imaging.However,the research of tomography three-dimensional imaging technology is not perfect,and needs more time development process from theoretical research to practical application.In recent years,the theory of compressive sensing solves the problem of large data storage and difficult transmission in the data acquisition,which must satisfy the Nyquist sampling theory.The theory points out that when the signal is sparse,the signal can be sampled and reconstructed by solving the nonlinear optimization problem with much less than the Nyquist sampling.In the 3-D of Tomographic SAR theoretical research,the number of observating object is far less than the vertical distance,and the number of the vertical distance is satisfied with the characteristics of spare,so the compressive sensing theory can apply to the 3-D of Tomographic SAR theorety.In this paper,there is an in-depth study on the 3-D of Tomographic SAR based on this theory.This paper firstly studies the geometric model and mathematical model of the tomographic SAR imaging,and according to the mathematical model of the tomographic SAR imaging,focuses on the research of the SAR 3D imaging method based on compressed sensing.Based on the theory of compressive sensing,several tomographic SAR imaging algorithms are studied in this paper,including orthogonal matching pursuit algorithm,regularized orthogonal matching pursuit algorithm,compressed sensing matching algorithm,generalized orthogonal matching pursuit algorithm.Based on the research and analysis of the algorithm,the simulation data and real data are used to validate these methods.The simulation data reflects the effectiveness of the algorithm.According to the process of SAR tomography imaging,the paper studies the SAR image registration method,validates it on the basis of the real data,and obtains a good registration effect.In the light of the verification of real data,this paper chooses the PanGu Seven Stars Hotel near the Bird's Nest in Beijing as the research object,and uses the TerraSAR-X data to carry on the experiment.The real data test result shows the rationality of the method in this paper.The innovations of this paper are as follows:(1)the method of image registration basedon correlation function is proposed.Firstly,the rough registration is performed,and then the block interpolation is used to improve the accuracy of image registration.(2)This paper uses orthogonal matching pursuit algorithm,regularized orthogonal matching pursuit algorithm,compressed sensing algorithm,generalized orthogonal matching algorithm for the simulation of compressed sensing,and analyzes the reconstruction results,besides evaluates the advantages and disadvantages of the above four algorithms.