Laboratory multistatic 3D SAR with polarimetry and sparse aperture sampling

IF 1.4 4区 管理学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Iet Radar Sonar and Navigation Pub Date : 2024-01-01 DOI:10.1049/rsn2.12528
Richard Welsh, Daniel Andre, Mark Finnis
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Abstract

With the advent of constellations of SAR satellites, and the possibility of swarms of SAR UAV's, there is increased interest in multistatic SAR image formation. This may provide advantages including allowing three-dimensional image formation free of clutter overlay; the coherent combination of bistatic SAR geometries for improved image resolution; and the collection of additional scattering information, including polarimetric. The polarimetric collection may provide useful target information, such as its orientation, polarisability, or number of interactions with the radar signal; distributed receivers would be more likely to capture any bright specular responses from targets in the scene, making target outlines distinct. Highlight results from multistatic polarimetric SAR experiments at the Cranfield University GBSAR laboratory are presented, illustrating the utility of the approach for fully sampled 3D SAR image formation, and for sparse aperture SAR 3D point-cloud generation with a newly developed volumetric multistatic interferometry algorithm.

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采用偏振测量和稀疏孔径采样的实验室多静态 3D SAR
随着合成孔径雷达卫星群的出现,以及合成孔径雷达无人机群的可能性,人们对多静态合成孔径雷达图像形成的兴趣日益浓厚。多静态合成孔径雷达图像形成的优势包括:可形成无杂波叠加的三维图像;双静态合成孔径雷达几何图形的连贯组合可提高图像分辨率;可收集更多散射信息,包括偏振信息。偏振收集可提供有用的目标信息,如目标的方位、偏振性或与雷达信号相互作用的次数;分布式接收器更有可能捕捉到场景中目标的任何明亮的镜面反射,使目标轮廓更加清晰。本文介绍了克兰菲尔德大学 GBSAR 实验室进行的多静态偏振合成孔径雷达实验的主要结果,说明了这种方法对全采样三维合成孔径雷达图像形成的实用性,以及利用新开发的体积多静态干涉测量算法生成稀疏孔径合成孔径雷达三维点云的实用性。
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来源期刊
Iet Radar Sonar and Navigation
Iet Radar Sonar and Navigation 工程技术-电信学
CiteScore
4.10
自引率
11.80%
发文量
137
审稿时长
3.4 months
期刊介绍: IET Radar, Sonar & Navigation covers the theory and practice of systems and signals for radar, sonar, radiolocation, navigation, and surveillance purposes, in aerospace and terrestrial applications. Examples include advances in waveform design, clutter and detection, electronic warfare, adaptive array and superresolution methods, tracking algorithms, synthetic aperture, and target recognition techniques.
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