IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v603y2022i7900d10.1038_s41586-022-04415-8.html
   My bibliography  Save this article

A large-scale microelectromechanical-systems-based silicon photonics LiDAR

Author

Listed:
  • Xiaosheng Zhang

    (University of California, Berkeley)

  • Kyungmok Kwon

    (University of California, Berkeley)

  • Johannes Henriksson

    (University of California, Berkeley)

  • Jianheng Luo

    (University of California, Berkeley)

  • Ming C. Wu

    (University of California, Berkeley)

Abstract

Three-dimensional (3D) imaging sensors allow machines to perceive, map and interact with the surrounding world1. The size of light detection and ranging (LiDAR) devices is often limited by mechanical scanners. Focal plane array-based 3D sensors are promising candidates for solid-state LiDARs because they allow electronic scanning without mechanical moving parts. However, their resolutions have been limited to 512 pixels or smaller2. In this paper, we report on a 16,384-pixel LiDAR with a wide field of view (FoV, 70° × 70°), a fine addressing resolution (0.6° × 0.6°), a narrow beam divergence (0.050° × 0.049°) and a random-access beam addressing with sub-MHz operation speed. The 128 × 128-element focal plane switch array (FPSA) of grating antennas and microelectromechanical systems (MEMS)-actuated optical switches are monolithically integrated on a 10 × 11-mm2 silicon photonic chip, where a 128 × 96 subarray is wire bonded and tested in experiments. 3D imaging with a distance resolution of 1.7 cm is achieved with frequency-modulated continuous-wave (FMCW) ranging in monostatic configuration. The FPSA can be mass-produced in complementary metal–oxide–semiconductor (CMOS) foundries, which will allow ubiquitous 3D sensors for use in autonomous cars, drones, robots and smartphones.

Suggested Citation

  • Xiaosheng Zhang & Kyungmok Kwon & Johannes Henriksson & Jianheng Luo & Ming C. Wu, 2022. "A large-scale microelectromechanical-systems-based silicon photonics LiDAR," Nature, Nature, vol. 603(7900), pages 253-258, March.
  • Handle: RePEc:nat:nature:v:603:y:2022:i:7900:d:10.1038_s41586-022-04415-8
    DOI: 10.1038/s41586-022-04415-8
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-022-04415-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41586-022-04415-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bing Chang & Teng Tan & Junting Du & Xinyue He & Yupei Liang & Zihan Liu & Chun Wang & Handing Xia & Zhaohui Wu & Jindong Wang & Kenneth K. Y. Wong & Tao Zhu & Lingjiang Kong & Bowen Li & Yunjiang Rao, 2024. "Dispersive Fourier transform based dual-comb ranging," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    2. Joel Siegel & Shinho Kim & Margaret Fortman & Chenghao Wan & Mikhail A. Kats & Philip W. C. Hon & Luke Sweatlock & Min Seok Jang & Victor Watson Brar, 2024. "Electrostatic steering of thermal emission with active metasurface control of delocalized modes," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    3. Saeed Sharif Azadeh & Jason C. C. Mak & Hong Chen & Xianshu Luo & Fu-Der Chen & Hongyao Chua & Frank Weiss & Christopher Alexiev & Andrei Stalmashonak & Youngho Jung & John N. Straguzzi & Guo-Qiang Lo, 2023. "Microcantilever-integrated photonic circuits for broadband laser beam scanning," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    4. Daniel Pérez-López & Ana Gutierrez & David Sánchez & Aitor López-Hernández & Mikel Gutierrez & Erica Sánchez-Gomáriz & Juan Fernández & Alejandro Cruz & Alberto Quirós & Zhenyun Xie & Jesús Benitez & , 2024. "General-purpose programmable photonic processor for advanced radiofrequency applications," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    5. Dong Liang & Cheng Zhang & Pengfei Zhang & Song Liu & Huijie Li & Shouzhu Niu & Ryan Z. Rao & Li Zhao & Xiaochi Chen & Hanxuan Li & Yijie Huo, 2024. "Evolution of laser technology for automotive LiDAR, an industrial viewpoint," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    6. Sudip Shekhar & Wim Bogaerts & Lukas Chrostowski & John E. Bowers & Michael Hochberg & Richard Soref & Bhavin J. Shastri, 2024. "Roadmapping the next generation of silicon photonics," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:603:y:2022:i:7900:d:10.1038_s41586-022-04415-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.