Despite an emerging interest in MIMO radar, the utilization of its complementary strengths in combination with optical depth sensors has so far been limited to far-field applications, due to the challenges that arise from mutual sensor calibration in the near field. In fact, most related approaches in the autonomous industry propose target-based calibration methods using corner reflectors that have proven to be unsuitable for the near field. In contrast, we propose a novel, joint calibration approach for optical RGB-D sensors and MIMO radars that is designed to operate in the radar's near-field range, within decimeters from the sensors. Our pipeline consists of a bespoke calibration target, allowing for automatic target detection and localization, followed by the spatial calibration of the two sensor coordinate systems through target registration. We validate our approach using two different depth sensing technologies from the optical domain. The experiments show the efficiency and accuracy of our calibration for various target displacements, as well as its robustness of our localization in terms of signal ambiguities.

翻译：尽管MIMO雷达日益受到关注，但由于近场环境下传感器间相互标定所面临的挑战，其与光学深度传感器互补优势的结合应用迄今仍局限于远场场景。事实上，自动驾驶领域大多数相关方法采用基于角反射器的目标标定方案，这些方法已被证明不适用于近场环境。与此相反，我们提出了一种新颖的光学RGB-D传感器与MIMO雷达联合标定方法，该方法专为雷达近场范围（距离传感器数分米内）设计。我们的流程包括：使用定制标定靶实现自动目标检测与定位，继而通过目标配准完成两个传感器坐标系的空间标定。我们采用两种不同的光学域深度传感技术验证了所提方法。实验结果表明，我们的标定方案在不同目标位移下均具有高效性与精确性，且其定位能力对信号模糊性具有鲁棒性。