Dual-Frequency Lidar for Compressed Sensing 3D Imaging Based on All-Phase Fast Fourier Transform

Authors

  • Xiaotian Li School of Optics and Photonics, Beijing Institute of Technology, China and Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of People's Republic of China, China
  • Yetong Hu School of Optics and Photonics, Beijing Institute of Technology, China and Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of People's Republic of China, China
  • Yuchen Jie School of Optics and Photonics, Beijing Institute of Technology, China and Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of People's Republic of China, China
  • Changming Zhao School of Optics and Photonics, Beijing Institute of Technology, China and Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of People's Republic of China, China
  • Zilong Zhang School of Optics and Photonics, Beijing Institute of Technology, China and Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of People's Republic of China, China

DOI:

https://doi.org/10.47852/bonviewJOPR32021565

Keywords:

compressed sensing, dual-frequency lidar, 3D imaging, all-phase FFT

Abstract

Lidar, with its advantages of high measurement accuracy, fine angular resolution, and strong anti-interference capability, plays a pivotal role in the field of scene depth information acquisition. Traditional approaches to achieving lateral spatial resolution in imaging include raster scanning and array detectors. The former necessitates frequent scanning to acquire depth maps, resulting in time consumption and instability. The latter encounters challenges such as high dark count rates, pixel crosstalk, and excessive costs for obtaining high-resolution images using array detectors. The introduction of compressed sensing (CS) offers a novel perspective on realizing non-scanning three-dimensional imaging. In this context, we propose a novel three-dimensional imaging system that combines compressed sensing with coherent dual-frequency continuous-wave lidar, and utilizes the all-phase fast Fourier transform to extract both amplitude and phase information. This system requires only M measurements, and through a reconstruction algorithm, it achieves the inversion of depth information for N-pixel scenes (M << N). Integrating cost-effective components such as digital micromirrors and single-point detectors, this affordable system accomplishes three-dimensional imaging of a single target. Notably, it significantly reduces the required number of measurements while concurrently ensuring enhanced eye safety and signal-to-noise ratio.

 

Received: 22 August 2023 | Revised: 20 November 2023 | Accepted: 23 November 2023

 

Conflicts of Interest
Zilong Zhang is an editorial board member for Journal of Optics and Photonics Research, and was not involved in the editorial review or the decision to publish this article. The authors declare that they have no conflicts of interest to this work.

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Published

2023-12-05

How to Cite

Li, X., Hu, Y., Jie, Y., Zhao, C., & Zhang, Z. . (2023). Dual-Frequency Lidar for Compressed Sensing 3D Imaging Based on All-Phase Fast Fourier Transform. Journal of Optics and Photonics Research. https://doi.org/10.47852/bonviewJOPR32021565

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Section

Research Articles