Wei Shaotang, Gao Bo, Wang Junya, You Zheng
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Research (Wash D C). 2025 Jun 23;8:0756. doi: 10.34133/research.0756. eCollection 2025.
Micro-electro-mechanical systems (MEMS) light detection and ranging (LiDAR) systems are widely employed in diverse applications for their precise ranging and high-resolution imaging capabilities. However, conventional Lissajous scanning patterns, despite their design flexibility, are increasingly limited in meeting the growing demands for image quality. In this study, we propose a novel programmable scanning method that enhances angular resolution within defined regions of interest (ROIs). By applying parameter modulation techniques, we establish a direct, analytical link between the scanning trajectory and ROI placement, enabling precise resolution control. The proposed method increases point cloud density by 2 to 6 times across any ROI within a Lissajous scan, achieving localized improvements of up to 650%, independent of frequency constraints. Moreover, it reduces the design complexity of MEMS scanning mirrors by half, while maintaining comparable high-resolution performance. Incorporating a gaze-inspired trajectory modulation strategy and random modulation continuous wave ranging, we develop a MEMS LiDAR prototype that greatly enhances point cloud fidelity and enables accurate 3-dimensional imaging within ROIs-achieving a ranging accuracy of 2.4 cm (3σ). This approach not only improves angular resolution in targeted regions but also extends the practical applicability of MEMS LiDAR to multitarget tracking and recognition scenarios. Furthermore, the study establishes a robust theoretical framework for ROI-based trajectory control, contributing to the advancement of next-generation high-resolution imaging systems.
微机电系统（MEMS）光探测与测距（LiDAR）系统因其精确测距和高分辨率成像能力而广泛应用于各种领域。然而，传统的李萨如扫描模式尽管设计灵活，但在满足日益增长的图像质量需求方面越来越受到限制。在本研究中，我们提出了一种新颖的可编程扫描方法，可在定义的感兴趣区域（ROI）内提高角分辨率。通过应用参数调制技术，我们在扫描轨迹与ROI放置之间建立了直接的分析联系，从而实现精确的分辨率控制。所提出的方法在李萨如扫描中的任何ROI上，将点云密度提高了2至6倍，实现了高达650%的局部改进，且不受频率限制。此外，它将MEMS扫描镜的设计复杂度降低了一半，同时保持了相当的高分辨率性能。结合受注视启发的轨迹调制策略和随机调制连续波测距，我们开发了一种MEMS LiDAR原型，该原型大大提高了点云保真度，并能够在ROI内实现精确的三维成像，测距精度达到2.4厘米（3σ）。这种方法不仅提高了目标区域的角分辨率，还将MEMS LiDAR的实际适用性扩展到多目标跟踪和识别场景。此外，该研究为基于ROI的轨迹控制建立了一个强大的理论框架，有助于推动下一代高分辨率成像系统的发展。
