In this article, we introduce a novel algorithm for efficient near-field synthetic aperture radar (SAR) imaging for irregular scanning geometries. With the emergence of fifth-generation (5G) millimeter-wave (mmWave) devices, near-field SAR imaging is no longer confined to laboratory environments. Recent advances in positioning technology have attracted significant interest for a diverse set of new applications in mmWave imaging. However, many use cases, such as automotive-mounted SAR imaging, unmanned aerial vehicle (UAV) imaging, and freehand imaging with smartphones, are constrained to irregular scanning geometries. Whereas traditional near-field SAR imaging systems and quick personnel security (QPS) scanners employ highly precise motion controllers to create ideal synthetic arrays, emerging applications, mentioned previously, inherently cannot achieve such ideal positioning. In addition, many Internet of Things (IoT) and 5G applications impose strict size and computational complexity limitations that must be considered for edge mmWave imaging technology. In this study, we propose a novel algorithm to leverage the advantages of non-cooperative SAR scanning patterns, small form-factor multiple-input multiple-output (MIMO) radars, and efficient monostatic planar image reconstruction algorithms. We propose a framework to mathematically decompose arbitrary and irregular sampling geometries and a joint solution to mitigate multistatic array imaging artifacts. The proposed algorithm is validated through simulations and an empirical study of arbitrary scanning scenarios. Our algorithm achieves high-resolution and high-efficiency near-field MIMO-SAR imaging, and is an elegant solution to computationally constrained irregularly sampled imaging problems.

翻译：本文提出了一种适用于不规则扫描几何的高效近场合成孔径雷达成像新算法。随着第五代毫米波设备的出现，近场SAR成像不再局限于实验室环境。定位技术的最新进展为毫米波成像的一系列多样化新应用带来了显著吸引力。然而，许多应用场景，如车载SAR成像、无人机成像以及智能手机手持成像，均受限于不规则扫描几何。传统近场SAR成像系统与快速人员安检扫描仪采用高精度运动控制器构建理想合成阵列，而前述新兴应用本质上无法实现此类理想定位。此外，众多物联网和5G应用对边缘毫米波成像技术施加了严格的尺寸与计算复杂度限制。本研究提出一种新型算法，旨在利用非合作SAR扫描模式、小型化多输入多输出雷达以及高效单站平面图像重建算法的优势。我们构建了一个数学框架以分解任意不规则采样几何，并提出一种联合解决方案来抑制多静态阵列成像伪影。通过仿真实验与任意扫描场景的实证研究验证了所提算法的有效性。该算法实现了高分辨率与高效率的近场MIMO-SAR成像，为计算资源受限的不规则采样成像问题提供了优雅解决方案。