基于多角度SAR的目标三维几何信息提取技术

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多基线多角度SAR高程信息提取技术

        经典 SAR 成像是将3D目标散射特征投影至2D（方位—距离）平面上，获得观测场景的2D SAR图像。然而，由于侧视成像几何的原因，这一投影将产生叠掩和阴影等问题，对 SAR 图像的分析和解译及目标的识别带来不利影响[1]。

        20世纪70年代，射电天文领域发展成熟的干涉技术被引入遥感领域，将覆盖同一地区的两张SAR影像联合处理并提取对应像素的相位差信息，以此恢复目标的数字高程模型（Digital Elevation Model, DEM），自此InSAR诞生[2]。InSAR 对基于两部或多部具有不同视角的天线获取的同一观测区域的数据进行处理，这些数据经过成像操作后将得到多幅聚焦的 SAR 复图像，正是这些复图像的相位差异可用于反演图像中目标几何信息，进而得到目标区域的DEM[3]，这一技术在检测地表形变等方面已经取得广泛应用。然而InSAR无法实现对观测对象的高程分辨，是一种2.5D技术，且受时空失相干[4]和大气延迟[5]的负面影响， 限制了其应用，尤其在长时间范围内地表缓慢累积形变探测应用中受到限制。

        针对相位失相干和大气延迟的负面影响，意大利Ferretti等人于2000年提出了永久散射体合成孔径雷达干涉( Persistent Scatterer InSAR，PSI) 技术[6]，并给出了数据建模与求解方法。该方法的核心思想是：使用在某一时间段内对同一地区获取的多幅SAR（即SAR影像时间序列），并使用统计分析方法测出成像区域内时间相关性较高的目标（即永久散射体），然后基于这些永久散射体目标的相位时间序列进行建模分析，从而分离形变与大气延迟信息[6]。PS是指在时间序列上具有稳定散射特性的地物(如裸露的岩石、建筑物和堤坝等) [7]，该方法利用二维周期图对PS弧段的高程误差差异及线性沉降速率差进行空间搜索，随后对PS目标的高程改正数及线性沉降速率进行重复迭代计算。在使用 PSI 技术进行形变提取时，如何从SAR影像时间序列中准确而高效地识别出真正的PS点直接影响形变和大气等参数的估计，因此选择高质量的PS点在PS干涉数据处理中十分重要[8]。但是PSI只考虑分辨单元内的一个散射体，不能解决叠掩问题[9]。

        雷达摄影测量（StereoSAR，又称Radar-grammetry）是雷达遥感提取DEM的一种重要方法，它利用不同角度、不同基线的SAR影像的幅度信息和立体像对的成像几何关系，通过求解距离-多普勒方程，来提取地面目标的三维信息[10]。但是SAR特有的侧视斜距成像方式及由此导致的透视收缩、叠掩和阴影等现象，造成SAR影像在地形起伏区域普遍存在着几何畸变[11]。由于成像视角不同，SAR立体像对中的几何畸变会呈现显著的差异，从而使得立体像对之间的匹配非常困难。因此，如何利用尽可能多的信息来提高匹配精度是一项值得考虑的事情[12]。

多角度SAR的目标三维几何信息重建技术

 

 

 

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