Multi-platform Synthetic Aperture Imaging in Complex Environments via Microlocal Techniques

通过微局部技术在复杂环境中的多平台合成孔径成像不同领域的多个进步有望将合成孔径成像技术从需要操作员的专用单一平台转变为大量自主操作的小平台。与单一的专用平台相比，这样的传感器群预计将提供数量级的性能提升。它们还有望在涉及动态变化场景和多次散射的复杂环境中运行。这种多平台合成孔径成像系统除了涉及复杂环境中的波传播外，还对成像提出了许多挑战。首先，对可伸缩性的要求意味着每个平台上的计算资源是有限的，而且平台之间可能不存在完美的阶段一致性。这意味着重建算法必须是快速、分散的，并且能够处理相位误差。其次，从图像重建的角度来看，平台的自主性意味着非理想的条件：传感器可能遍历任意轨迹，传输不同的波形等。这些挑战排除了使用标准层析成像方法的可能性。本研究涉及开发理论基础和相应的构造算法来应对多平台合成孔径成像的挑战。该项目的基本发展适用于所有基于散射场的合成孔径成像模式，包括射频和声学。该项目的核心是微局部分析。这一理论导致了强大的广义滤波反投影(GFBP)技术，它可以适应复杂环境下的非理想成像条件和波传播模型。该项目研究了微局部技术的创新扩展，并将其与逆散射理论和统计估计和检测理论相结合。具体地说，研究人员研究了在动态变化和多次散射环境中成像的GFBP算法；解析自动聚焦方法和快速GFBP算法。

Multi-platform Synthetic Aperture Imaging in Complex Environments via Microlocal TechniquesMultiple advances in diverse fields are expected to transition synthetic-aperture imaging technology from a dedicated single platform requiring an operator to a large number of small platforms operating autonomously. Such a swarm of sensors is expected to provide orders-of-magnitude performance gains relative to a single, dedicated platform. They are also expected to operate in complex environments involving dynamically changing scenes and multiple scattering. Such multi-platform synthetic-aperture imaging systems pose a number of challenges to image formation in addition to those involving wave propagation in complex environments. First, the requirement for scalability implies that the computational resources at each platform are limited and that moreover there may not be perfect phase coherency between platforms. This means the reconstruction algorithms have to be fast, decentralized and be able to handle phase errors. Second, the autonomy of the platforms implies non-ideal conditions from the perspective of image reconstruction: the sensors may be traversing arbitrary trajectories, and transmitting varying waveforms, etc. These challenges rule out the use of standard tomographic methods.This research involves developing theoretical foundations and corresponding constructive algorithms to address the challenges of multi-platform synthetic-aperture imaging. The fundamental developments of this project are applicable to all scattered-field-based synthetic-aperture imaging modalities, including RF and acoustics. Central to the project is microlocal analysis. This theory leads to powerful Generalized Filtered-BackProjection (GFBP) techniques that can accommodate non-ideal imaging conditions and wave propagation models for complex environments. This project investigates innovative extensions to microlocal techniques and integrates them with inverse scattering theory and statistical estimation and detection theory. Specifically, the investigators study GFBP algorithms for imaging in dynamically changing and multiple-scattering environments; analytic autofocus methods and fast GFBP algorithms.