【作者】 刘齐发；

【导师】 聂明新；

【作者基本信息】 武汉理工大学 ， 通信与信息系统， 2008， 硕士

【摘要】 随着合成孔径雷达越来越广泛应用,人们对雷达图像的分辨率的要求也越来越高。但在通过改进和更新硬件技术来提高图像分辨率已经成为一个难以突破的瓶颈的今天,如何利用数字信号处理技术来提高图像的分辨率就显得十分重要了。对于合成孔径雷达(SAR)系统来说,雷达与目标之间的相对运动,既是成像的前提条件,也是导致图像模糊的根源。一方面,运动提供了成像所需要的含有多普勒信息的回波信号:另一方面,运动的不确定性造成的相位误差,又是高分辨率的制约因素。随着对分辨率要求的提高,在孔径合成时间内,对天线相位中心与成像目标之间运动补偿精度的要求也相应地提高了。即便是经过高精度的运动补偿,由于成像算法上的近似,以及大气传播效应等产生的相位误差仍会造成散焦,导致图像的恶化。因此,为得到聚焦良好的图像,在利用惯导数据进行运动补偿之后,高分辨成像往往还要求从SAR回波数据中估计并补偿残余的相位误差,这一过程称为自聚焦。在合成孔径雷达成像算法中,利用自聚焦算法估计雷达回波信号的多普勒参数来校正相位误差是必不可少的一个步骤,相位梯度自聚焦(PGA)算法因其较好的稳健性而得到广泛应用。经典的相位梯度自聚焦算法选择能量较高距离单元中的最强散射点作为特显点进行多普勒参数估计。但由于背景杂波和相邻目标的干扰,采用这种策略挑选出的强散射点往往不是孤立的,这将导致相位误差估计的准确性下降。本文在从理论上分析了经典相位梯度自聚焦算法不足的基础上,提出了一种改进算法:将幅度较大的散射点与周围背景区的均值相比较,以该比值作为该像素点质量的评估,选取比值较大的点作为特显点,这样选取的特显点一般都是孤立的。利用这种孤立特显点来估计相位误差,其准确性会得到很大提高,图像的聚焦效果也得到了改善,尤其是可以将有强背景杂波情况下相位梯度自聚焦算法的聚焦效果大幅度地提高。论文最后还通过仿真对改进算法进行了验证,并分析了实验结果与改进算法的性能。更多还原

【Abstract】 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.更多还原