| 一种基于曲线SAR的三维目标特征提取与自聚焦新算法 |
| |
| 引用本文： | 吴仁彪,苏志刚,刘家学,刘杰.一种基于曲线SAR的三维目标特征提取与自聚焦新算法[J].遥感学报,2002,6(6):490-495. |
| |
| 作者姓名： | 吴仁彪 苏志刚 刘家学 刘杰 |
| |
| 作者单位： | 中国民用航空学院,通信与信息处理研究所,天津,300300 |
| |
| 基金项目： | 国家自然科学基金项目（69902009），国家863高技术计划项目（863-308-19-01-（3））资助课题。 |
| |
| 摘 要： | 曲线合成孔径雷达（Curvilinear Synthetic Aperture Radar,简称曲线SAR）是一种新的三维成像模式，通过让载机作曲线飞行，曲线SAR系统能同时在方位维和高度维形成大的合成孔径。本文提出一种曲线SAR的三维目标特征提取和自聚焦新方法。新方法是建立在一种灵活的接收数据模型之上的参数化的新方法。仿真实验证明了所提方法的有效性。
|
| 关 键 词： | 合成孔径雷达 曲线合成孔径雷达 运动补偿 三维特征 提取 数据模型 自聚焦算法 |
| 文章编号： | 1007-4619(2002)06-0490-06 |
| 收稿时间： | 5/1/2002 12:00:00 AM |
| 修稿时间： | 2002年5月1日 |
A Novel Autofocus and 3-D Target Feature Extraction Algorithm for Curvilinear SAR |
| |
| WU Ren-biao,SU Zhi-gang,LIU Jia-xue and LIU Jie.A Novel Autofocus and 3-D Target Feature Extraction Algorithm for Curvilinear SAR[J].Journal of Remote Sensing,2002,6(6):490-495. |
| |
| Authors: | WU Ren-biao SU Zhi-gang LIU Jia-xue and LIU Jie |
| |
| Abstract: | By transmitting signals with large bandwidth and utilizing the relative motion between the radar and the objects to be imaged, synthetic aperture radar(SAR) can produce high-resolution images of targets or scenes of interest. Now, SAR imaging technology has been widely used in many military and civilian applications, such as battlefield awareness, environment monitoring,and city planning. Today, over thirty SAR systems have been put into operation and more are being built around the world. However,most of them can only produce two-dimensional(2-D)SAR images. In practice, 3-D SAR images and 3-D target feature extraction are needed for many applications. The 3-D features of a target scatterer include the radar cross-section (RCS) ,the 2-D location (range and cross-range) and the height(the third dimensional parameter)of the scatterer.Very few papers have discussed the 3-D target feature extraction problem. A popular approach to extract the 3-D target features is interferometric SAR(IFSAR) , which uses a pair of vertically displaced antennas to obtain coherent and parallel measurement apertures. IFSAR can be used to measure the height but has no resolution capability along the height dimension since it only provides two vertical parallel apertures. Hence IFSAR is only a 2.5-D imaging system. Moreover, in IFSAR, the height measurement involves the troublesome phase unwrapping procedure. Recently, Knaell proposed a new idea for the extraction of 3-D target features, which is based on curvilinear SAR(CLSAR) . Unlike the conventional SAR or IFSAR, whose flight trajectory is a straight line, the flight path of a CLSAR system is curve-shaped. CLSAR can be used to form synthetic apertures both in the azimuth and in the height dimensions. Hence CLSAR has resolution capability in the height dimension and the height ambiguity problem encountered in IFSAR is avoided.There are two challenging issues associated with CLSAR. First, the flight path of CLSAR cannot be controlled or measured accurately and the autofocus task here is more complicated than the conventional SAR systems. Second, the aperture of a CLSAR is like a sparse array. The spread function of a point scatterer has high sidelobes and hence the images obtained with conventional Fourier analysis have artifacts. We must carefully devise the feature extraction algorithm so that meaningful features can be extracted.Recently,Wu et al . have proposed a unified robust autofocus algorithm for the conventional 2-D SAR and ISAR imaging. In this paper,we have successfully extended them to the simultaneous autofocus and 3-D target feature extraction via CLSAR. The new algorithm is a parametric approach but is based on a flexible data model and a robust parameter estimation algorithm. The aucofocus is achieved by enhancing the focusing of the dominant scatterers of the target. The advantages of the new algorithm over existing autofocus algorithms include: 1) selecting the dominant scatterers of a target automatically in the 3-D image domain, 2) eliminating the necessary condition of a target containing well isolated or very dominant scatterers, 3) combining the phase and radar cross section information from the selected scatterers optimally by minimizing a nonlinear least squares cost function, and 4) avoiding the burdensome phase unwrapping step, The new approach can be used to significantly improve the estimation accuracy of the target features. Numerical examples are provided to illustrate the performance of the proposed algorithm. |
| |
| Keywords: | synthetic aperture radar curvilinear synthetic aperture radar motion compensation feature extrac-tion |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《遥感学报》浏览原始摘要信息 |
| 点击此处可从《遥感学报》下载免费的PDF全文 |
|
