Non-Canonical Integral Transforms for Multistatic Synthetic Aperture Radar (SAR) and Video SAR (VSAR) for Target Motion

用于目标运动的多基地合成孔径雷达 (SAR) 和视频 SAR (VSAR) 的非规范积分变换

• 批准号: 2905381
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2905381
• 关键词: Non; Canonical; Integral; Transforms; Multistatic

This PhD will generate and validate innovative algorithms for the formation of images of dynamic scenes from multistatic Synthetic Aperture Radar (SAR), i.e. VSAR. The PhD will be jointly funded by Dstl and an EPSRC iCASE Award. Dstl's Future Sensing Programme (FSP) seeks to drive game-changing and novel Science & Technology (S&T) within the radar field; it develops novel technologies and techniques that could deliver operational advantage and freedom of action in the future. One particular area of interest is the improvement of radar imagery. The majority of monostatic SAR image formation schemes utilise a line integral approach. However elliptical/ellipsoidal, circular and spherical integral transforms can be utilised to mathematically model bi-static/multi-static systems. This, coupled with iterative reconstruction and novel regularisation schemes, will tackle complex scattering phenomenology, resulting in fine resolution images and providing more information about the scene - such as about anisotropic scatterers. This PhD is required to consider SAR image formation of dynamic scenes. In mono- and bi-static SAR, objects moving at a constant speed in the azimuth direction will appear blurred due to the change in position between each radar pulse, while those moving in the radial direction will be focussed but appear displaced in azimuth. Accelerating and manoeuvring objects further add to the complexity. Both theoretical and practical numerical methods will be developed to understand how multi-static and other high-dimensional data can be used to resolve this otherwise ambiguous inverse

该博士将生成和验证创新算法，以形成来自多阶段合成孔径雷达（SAR）的动态场景图像，即VSAR。博士将由DSTL共同资助和EPSRC ICASE奖。 DSTL的未来传感计划（FSP）试图在雷达领域推动改变游戏规则和新颖的科学技术（S＆T）；它开发了新颖的技术和技术，可以在未来提供运营优势和行动自由。感兴趣的一个特定领域是雷达图像的改善。大多数单声道SAR图像形成方案都采用线路积分方法。然而，椭圆/椭圆形，圆形和球形积分变换可用于数学对双静态/多静态系统进行建模。加上迭代重建和新颖的正则化方案，将解决复杂的散射现象学，从而产生精细的分辨率图像，并提供有关场景的更多信息，例如关于各向异性散射器。该博士必须考虑动态场景的SAR图像形成。在单静态和双静态SAR中，由于每个雷达脉冲之间的位置变化，在方位角以恒定速度移动的物体会显得模糊，而沿径向方向移动的对象将聚焦但在方位角中显得位移。加速和操纵对象进一步增加了复杂性。将开发理论和实用的数值方法，以了解如何使用多静态和其他高维数据来解决这种否则模棱两可的倒数