大斜视条带合成孔径雷达成像信号处理研究

发布时间：2018-07-25 07:12

【摘要】：合成孔径雷达(Synthetic Aperture Radar,SAR)常用的成像模式有聚束模式,条带模式和扫描模式。相对于聚束模式,条带模式有能够进行连续大面积成像的优点。通常情况下,条带SAR工作于正侧视模式。但许多应用场合,需将波束向前或向后斜视,从而获得雷达平台前方或后方的场景图像,即采用斜视模式进行雷达成像。斜视模式是重要的条带SAR成像模式之一,具有很高的军事应用价值。然而,大斜视情况下的条带合成孔径雷达成像信号处理研究还不是很成熟,目前主要面临两个显著的困难。一是大斜视角导致严重的距离方位耦合,二是对于全孔径条带SAR数据的处理,实时实现困难。极坐标格式算法(Polar Format Algorithm,PFA)采用极坐标格式存储数据,其成像精度与斜视角无关,能够有效解决大斜视条件下的高精度成像问题。而且,PFA与其他成像算法相比,算法简洁高效,且适用于复杂雷达航迹,因此在大机动/大斜视条件下具有很好的应用前景。但是,PFA算法为经典的聚束模式SAR成像算法,不能直接用于对条带SAR数据进行处理。本文通过将全孔径条带SAR数据进行子孔径划分,在子孔径内采用改进的极坐标格式算法进行聚焦成像处理,然后对各子孔径成像结果进行无缝拼接实现大斜视条带SAR高精度实时成像处理。论文的主要工作如下:论文第一章绪论,从研究背景和意义出发,回顾了SAR技术及起源,分析了国内外SAR成像技术研究现状,并介绍了本文的主要工作和结构。论文第二章对PFA算法展开研究。首先介绍PFA成像原理,然后介绍了PFA几何模型,并从距离徙动校正角度分析了极坐标格式转换过程,对PFA成像算法进行了点目标仿真验证。从分析波前弯曲效应出发,对几何失真校正进行研究并对几何失真校正效果进行了点目标仿真验证。论文第三章研究条带SAR数据的子孔径聚束处理。首先,对条带模式SAR与聚束模式SAR进行比较,分别对条带SAR信号模型和聚束SAR信号模型进行分析研究。然后对条带模式-聚束模式数据的转换原理进行阐述。随后采用经典的PFA算法对条带SAR进行子孔径聚束成像,并经过子孔径图像的空变后滤波处理及几何失真校正处理,得到子孔径PFA图像。最后通过仿真结果验证了子孔径条带数据的PFA成像算法的有效性。论文第四章研究条带SAR数据的拼接成像处理。提出了一种基于PFA的大斜视条带SAR子孔径拼接成像处理算法,利用改进的PFA成像算法,解决了子孔径内大斜视高精度成像困难的问题,通过子孔径图像的拼接成像原理,来实现全孔径的实时成像。通过点目标仿真及实测数据处理验证了提出算法的有效性。最后,结束语对全文的工作进行了总结,并对下一步需要继续研究的问题做出了展望。
[Abstract]:The usual imaging modes of synthetic Aperture Radar (Synthetic Aperture) are bunching mode, stripe mode and scanning mode. Compared with the bunching mode, the strip mode has the advantage of continuous large area imaging. In general, the strip SAR works in positive side-looking mode. However, in many applications, the beam should be strayed forward or backward to obtain the scene image in front or rear of the radar platform, that is, the squint mode is used for radar imaging. Strabismus is one of the most important SAR imaging modes, which has high military application value. However, the imaging signal processing of striped synthetic aperture radar (SAR) with large squint is not very mature, and it faces two significant difficulties. One is that the large oblique angle results in serious azimuth coupling and the other is the difficulty of processing the full aperture strip SAR data in real time. Polar coordinate format algorithm (Polar Format algorithm) uses polar coordinate format to store data, and its imaging accuracy is independent of oblique angle of view, which can effectively solve the problem of high-precision imaging under the condition of large squint. Compared with other imaging algorithms, PFA is simple and efficient, and suitable for complex radar tracks, so it has a good prospect in large maneuvering / large squint. However, the SAR algorithm is a classical bunch-mode SAR imaging algorithm, which can not be directly used to process strip SAR data. In this paper, by dividing the full aperture strip SAR data into sub-aperture, the improved polar format algorithm is used for focusing imaging in the sub-aperture. Then the subaperture imaging results are jointed seamlessly to realize the high precision real-time imaging processing of large squint strip SAR. The main work of the thesis is as follows: the first chapter introduces the background and significance of the research, reviews the SAR technology and its origin, analyzes the current research situation of SAR imaging technology at home and abroad, and introduces the main work and structure of this paper. In the second chapter, the PFA algorithm is studied. Firstly, the principle of PFA imaging is introduced, then the geometric model of PFA is introduced. The polar coordinate format conversion process is analyzed from the angle of range migration correction, and the point target simulation of PFA imaging algorithm is carried out. Based on the analysis of wavefront bending effect, the geometric distortion correction is studied and the point target simulation is carried out to verify the effect of geometric distortion correction. In chapter 3, the subaperture bunching processing of strip SAR data is studied. Firstly, the paper compares strip mode SAR with spotlight mode SAR, and analyzes the signal model of strip SAR and spotlight SAR respectively. Then, the conversion principle of strip pattern-spotlight mode data is expounded. Then the classical PFA algorithm is used to perform the sub-aperture bunching imaging of the strip SAR, and the subaperture PFA image is obtained by the space-variant filtering and geometric distortion correction of the sub-aperture image. Finally, the effectiveness of the PFA imaging algorithm based on sub-aperture strip data is verified by simulation results. In chapter 4, the stitching imaging of strip SAR data is studied. A large squint strip SAR subaperture stitching algorithm based on PFA is proposed. By using the improved PFA imaging algorithm, the problem of high precision imaging with large squint in the subaperture is solved, and the principle of subaperture image stitching is adopted. To achieve full aperture real-time imaging. The effectiveness of the proposed algorithm is verified by point target simulation and data processing. Finally, the conclusion summarizes the work of this paper, and makes a prospect for the further research.
【学位授予单位】：南京航空航天大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN957.52

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