Research On Compressed Sensing Multi-baseline Spaceborne SAR Image Simulation And Three-dimensional Imaging

Multi-baseline synthetic aperture radar imaging technology is the extension oftwo-dimensional SAR imaging techniques. Because of the multiple navigationthrough the tomographic up for synthetic aperture based on the type of incidentangles can get the resolution of height. In recent years, the tomography algorithm, athome and abroad, becomes a research hotspot of SAR technology.As the development of new technology in recent years, compressed sensingtheory states that when the signal has a sparse time, the signal sampling andreconstruction can be much lower than the Nyquist sampling theorem by solving anonlinear optimization problem. The main steps can be divided into three parts, theyare signal sparse representation, random projection and signal reconstruction.The main work and innovations are as follows:Since three-dimensional SAR imaging based on the multiple images, theproblems such as shift, compression and distortion will inevitably occur while thelocation for sailing obtained at different image. So we studied the pixel-levelcorrelation function method for image registration. Experimental verification byinterfering with the accuracy of the proposed method and feasibility.Since the SAR scene with sparse, we can reduce the amount of data and have anideal result for the imaging. The result of the simulation experiment shows theeffectiveness when compared with the RD algorithm.SAR tomography for the current three-dimensional imaging technique mainlybased on Fourier transform method (MUSIC, APES, etc.) to a highly focusedapproach, however, spaceborne actual situation may lead to an insufficient numberof non-uniform baseline, and the traditional three-dimensional imaging methoddifficult to meet the requirements. So we study the sparse baseline tomographicimaging method based on compressed sensing. And the experimental simulationresults verified the effectiveness of the algorithm.