Improving The Imaging Resolution Of SAR Based On The Theory Of Advanced Digital Signal Processing

Nowadays, the Synthetic aperture radar (SAR) is applied increasingly in the more and more fields, and so, the requirement of developing high-resolution of the SAR is more and more intense.But in today when it is a bottleneck to promote the resolution with improving and updating the hardware configuration, it seems very important how to improve the resolution by the technology of advanced digital signal processing.For SAR, imaging is based on the relative movement of the radar and the target, but it is the relative movement that causes the imaging indistinction. On the one hand, the Doppler message in the echo signal is provided by the relative movement, and on the other hand, the imaging high-resolution is restricted by the phase error issued from the nondeterminacy of the relative movement. Along with the requirement of the high-resolution, the accuracy of compensating the motion errors must to be improved. Yet even this, the phase error brought by the atmospheric propagation error and the approximating of imaging algorithms is still a one of the dominating reasons decreasing imaging quality and causing image out-of-focus. So, in order to get a clear image, estimating and compensating the phase error from the echo signal of SAR after compensating the motion errors by high-precision INS which is called autofocus is essential.In all imaging algorithms of SAR, using autofocus algorithms to estimate the Doppler parameters to compensate the phase errors is a crucial step. And in these autofocus algorithms, the phase gradient autofocus (PGA) algorithm is frequently used because of it's robustness. In PGA algorithms, the powerfull scatter in range unit possessing more energy is selected to estimate the Doppler parameters as the dominant scatter. But if the scatter selected in PGA algorithm is not isolated because of the interference caused by background noise and adjacent target, the accuracy of the phase error estimation will be degraded.In this dissertation, after analyzing the limitation of the classical PGA algorithms, an improved PGA algorithm is presented to select an isolated scatter. And in this improved PGA algorithm, each rather too powerfull pixel in the image is evaluated, and then the high quality scatters are selected for the phase error estimation.A simulational experimentation is designed to verify the performance of the improved algorithm in the end of this dissertation. And the results of experimentation show that the improved PGA algorithm can elevate the accuracy of the phase error estimation.