Synthetic Aperture Radar Imaging Algorithm And The Side Lobe Suppression Technique

Synthetic Aperture Radar (SAR) imaging is not affected by factors such as climate, day and night, and it has the advantage of all-condition and all-time. Therefore it has broad applications in both military and civil fields.The efficient imaging algorithm is the pivotal and the foundation of SAR imaging. In this thesis, three imaging algorithms are studied following the analysis of the basic principles of SAR imaging, including Range-Doppler (RD) algorithm, Chirp Scaling algorithm and Range Migration algorithm. Considering the characteristics of the large squint side-looking SAR, improved algorithms are discussed. The simulation results confirm the algorithms validity.The two-dimensional image of the linear frequency modulation SAR echo signal obtained after SAR image processing has the high side-lobe level. This problem will seriously affect the target detection and maybe cause a false alarm nearby the small side-lobe, so it is important to suppress the side-lobe. The traditional side-lobe suppression usually uses amplitude weighting technique, meanwhile, it also brings the problem of stretching width of the main lobe, so it seriously influences SAR image quality. As for this problem, the thesis discusses two methods for side lobe suppression proposed by means of the radial basis function networking technology and the Tikhonov regularization method based on genetic algorithm. Their principle and performance are analyzed and discussed. The theoretical analysis and the simulation results show that these two methods are improved in side-lobe suppression of echo signal.