大斜视下SAR成像算法及旁瓣抑制技术研究

发布时间：2018-07-06 09:21

本文选题：合成孔径雷达 + 极坐标格式算法　；参考：《西安电子科技大学》2014年硕士论文

【摘要】：合成孔径雷达(SAR)作为一种高分辨率成像雷达,在当代遥感成像领域发挥着重要的作用,是重要的成像工具之一。它能够获得高质量,高分辨率的图像,在国防事业和国民的日常生活中得到了广泛的应用。然而,随着现代军事武器的发展和人们对生活质量要求的提高,SAR成像技术及图像处理技术一直是学者们研究的热点话题。迄今为止,虽然雷达成像技术领域已经提出了很多有效的SAR成像及图像处理方法,但在实际应用中,由于成像目标强度的多样化和成像场景的复杂化,SAR成像技术及图像处理技术仍然面临着巨大的挑战。本文针对场景中存在很多强目标点的情况进行了详细的分析研究,主要研究成果如下:1.提出了一种基于旋转坐标系的极坐标格式算法(MPFA)。该方法适用于大斜视情况,它是以极坐标格式算法(PFA)为基础,将SAR成像的几何坐标系旋转斜视角度,在旋转坐标系下重新计算合成孔径雷达的坐标,然后获取雷达与目标点之间的距离。通过几何坐标系的旋转,将斜视情况下的几何模型转化到了正侧视情况下的模型,该方法的提出不但克服了PFA只适用于正侧视的缺陷,而且使成像目标在大斜视情况下仍为正十字状,为后续的SAR图像旁瓣抑制工作奠定了便利基础。2.提出了一种基于模值约束的空间变迹法(CMoSVA)。该方法是基于经典的空间变迹法(SVA)的几何模型,通过使用模值滤波的方法使得每一像素点的能量最小,根据这一原则,计算出加权因子,接着提出了约束因子的概念,最后将加权因子与约束因子进行比较,根据不同的比较结果,得出不同像素点的输出值。该方法不仅使旁瓣的能量抑制到更低,而且拥有了更窄的主瓣,提高了SAR图像的分辨率。于此同时,该方法也存在一定的缺陷,该方法降低了整幅图像的能量,换句话说就是,处理后的图像相比于原始图像变得比较暗。所以,在应用旁瓣抑制处理之后,为了解决图像能量因旁瓣抑制而受影响的缺陷,又加入了SAR图像背景滤波技术。首先,提取原始SAR图像的背景,然后将已通过上述旁瓣抑制方法处理后的图像中比较暗的背景替换为原始图像的背景,通过上述处理就可以得到一幅高质量,高分辨率的SAR图像。本文工作得到了国家自然科学基金(No.61173092)、新世纪优秀人才支持计划(No.66ZY110)和陕西省科学技术研究发展计划项目(No.2013KJXX-64)资助。
[Abstract]:Synthetic Aperture Radar (SAR), as a high-resolution imaging radar, plays an important role in the field of remote sensing imaging and is one of the important imaging tools. It can obtain high-quality and high-resolution images and is widely used in national defense and daily life. However, with the development of modern military weapons and the improvement of quality of life (QOL), SAR imaging technology and image processing technology has been a hot topic for scholars. So far, although many effective SAR imaging and image processing methods have been proposed in the field of radar imaging technology, but in practical applications, Because of the diversity of imaging target intensity and the complication of imaging scene, SAR imaging technology and image processing technology are still facing great challenges. This paper makes a detailed analysis and research on the situation where there are many strong target points in the scene. The main research results are as follows: 1. A polar coordinate format algorithm (MPFA) based on rotating coordinate system is proposed. This method is suitable for large squint. Based on Polar format algorithm (PFA), the coordinate of synthetic aperture radar (SAR) is recalculated in the rotating coordinate system by using the geometric coordinate system of SAR imaging. The distance between the radar and the target point is then obtained. Through the rotation of the geometric coordinate system, the geometric model in strabismus is transformed into the model in the positive side view. This method not only overcomes the defect that PFA is only suitable for the positive side view. Moreover, the imaging target is still a positive cross in the case of large squint, which lays a convenient foundation for the next SAR image sidelobe suppression. In this paper, a new method of spatial transformation based on modulus constraint (CMoSVA) is proposed. The method is based on the classical geometric model of SVA. The energy of each pixel is minimized by using the modular filtering method. According to this principle, the weighting factor is calculated, and the concept of constraint factor is proposed. Finally, by comparing the weighting factor with the constraint factor, the output values of different pixel points are obtained according to the different comparison results. This method not only reduces the energy of the sidelobe to a lower level, but also has a narrower main lobe, which improves the resolution of SAR images. At the same time, the method also has some defects, the method reduces the energy of the whole image, in other words, the processed image becomes darker than the original image. Therefore, after applying sidelobe suppression, in order to solve the problem that the image energy is affected by sidelobe suppression, the background filtering technology of SAR image is added. Firstly, the background of the original SAR image is extracted, then the dark background in the image processed by the sidelobe suppression method is replaced with the background of the original image, and a high quality image can be obtained by the above processing. High resolution SAR images. This work is supported by the National Natural Science Foundation of China (No. 61173092), the New Century Talent support Program (No. 66ZY110) and the Shaanxi Province Scientific and technological Research and Development Program (No. 2013KJXX-64).
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.52

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