压缩感知在城区高分辨率SAR层析成像中的应用

压缩感知在城区高分辨率SAR 层析成像中的应用

廖明生* 魏恋欢 汪紫芸 Timo Balz 张 路

(武汉大学测绘遥感信息工程国家重点实验室 武汉 430079)

摘 要：在建筑密集的城区复杂场景中，高分辨率SAR 影像中存在严重的叠掩效应，影像解译的难度加大。SAR 层析成像可以分离单个分辨单元内混叠的散射体目标，并且获取各个散射体的3维位置和后向散射强度。该文首先论述了3维SAR 层析成像的基本原理，针对传统谱估计法获得的高程向分辨率较低的问题，综述了压缩感知方法在城区3维SAR 层析成像中的应用，以基追踪和双步迭代收缩阈值法为例，开展了TerraSAR-X 聚束模式数据实验，并与传统的奇异值阈值法进行了对比分析。研究结果表明压缩感知方法的高程向超分辨率、旁瓣抑制优势明显，在城区SAR 层析成像中具有广阔的应用前景。

关键词：SAR 层析成像；压缩感知(CS)；稀疏重建；基追踪；双步迭代收缩阈值；超分辨率

中图分类号：TN958 文献标识码：A 文章编号：2095-283X(2015)02-0123-07DOI: 10.12000/JR15031

引用格式：廖明生, 魏恋欢, 汪紫芸, 等. 压缩感知在城区高分辨率SAR 层析成像中的应用[J]. 雷达学报, 2015,4(2): 123–129. /10.12000/JR15031.

Compressive Sensing in High-resolution 3D SAR

Tomography of Urban Scenarios

Liao Ming-sheng Wei Lian-huan Wang Zi-yun Timo Balz Zhang Lu

(State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing ,

Wuhan University , Wuhan 430079, China )

Abstract : In modern high resolution SAR data, due to the intrinsic side-looking geometry of SAR sensors,layover and foreshortening issues inevitably arise, especially in dense urban areas. SAR tomography provides a new way of overcoming these problems by exploiting the back-scattering property for each pixel. However,traditional non-parametric spectral estimators, e.g. Truncated Singular Value Decomposition (TSVD), are limited by their poor elevation resolution, which is not comparable to the azimuth and slant-range resolution.In this paper, the Compressive Sensing (CS) approach using Basis Pursuit (BP) and TWo-step Iterative Shrinkage/Thresholding (TWIST) are introduced. Experimental studies with real spotlight-mode TerraSAR-X dataset are carried out using both BP and TWIST, to demonstrate the merits of compressive sensing approaches in terms of robustness, computational efficiency, and super-resolution capability.

Key words : SAR tomography; Compressive Sensing (CS); Sparse reconstruction; Basis pursuit; TWo-step Iterative Shrinkage/Thresholding (TWIST); Super resolution

1 引言

星载SAR 传感器在过去几十年中不断更新换代，实现了从无到有、从中低分辨率到高分辨率的

升级，在城区复杂场景目标解译方面展现出巨大的应用潜力[1]。在高分辨率情况下，我们可获取的目标特征信息越来越丰富，其结构、形状、纹理等细节信息也更为突出；但另一方面，由于目标结构的复杂性，城区地物目标互相遮挡引起的多次散射、叠掩和阴影等现象更加明显，使得目标/场景仍然难以识别和解译[2,3]。

第4卷第2期雷 达 学 报Vol. 4No. 22015年4月Journal of Radars Apr. 2015

2015-03-11收到，2015-04-09改回；2015-04-24网络优先出版

国家自然科学基金(61331016, 41174120)和高等学校博士学科点专项科研基金(20110141110057)资助课题*通信作者： 廖明生 liao@

Reference format: Liao Ming-sheng, Wei Lian-huan, Wang Zi-yun, et al.. Compressive sensing in high-resolution 3D SAR tomography of urban scenarios[J]. Journal of Radars , 2015, 4(2): 123–129. /10.12000/JR15031.