ToF vs. FMCW LiDAR

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ToF is still better in the short term

Recent papers1–5 have presented a number of marketing claims about the benefits of Frequency Modulated Continuous Wave (FMCW) LiDAR systems. As might be expected, there is more to the story than the headlines claim. This white paper examines these claims and offers a technical comparison of Time of Flight (TOF) vs. FMCW LiDAR for each of them. We hope this serves to outline some of the difficult system trade-offs a successful practitioner must overcome, thereby stimulating robust informed discussion, competition, and ultimately, improvement of both TOF and FMCW offerings to advance perception for autonomy.

AEye believes that high shot-rate, agile-scanning TOF systems serve the needs of autonomous vehicle LiDAR more effectively than FMCW when cost, range, performance, and point cloud quality are important. However, it is not hard to see the logical reasoning where FMCW could play a niche role in applications where lower shot rates are suitable and FMCW systems are more economical. While there will be nice videos of FMCW and other low TRL systems in well controlled environments with expensive prototypes, it’s a whole different world when taking harsh environments and mass production into account. We hope this white paper will stimulate development and awareness in both TOF and FMCW systems, increasing the component options for perception engineers everywhere. More info https://www.aeye.ai/technology/time-of-flight-vs-fmcw-lidar-a-side-by-side-comparison/

References

  1. Aurora Team, “FMCW Lidar: The Self-Driving Game-Changer”, www.medium.com, April 9, 2020
  2. Philip Ross, “Aeva Unveils Lidar on a Chip”, IEEE Spectrum, December 11, 2019.
  3. Timothy Lee, “Two Apple veterans built a new lidar sensor — here’s how it works”, arsTECHNICA, October 2, 2018.
  4. Jeff Hect, “Lasers for Lidar: FMCW lidar: An alternative for self-driving cars”, LaserFocusWorld, May 31st, 2019.
  5. “Aeva launches ‘4D’ LiDAR on chip for autonomous driving”, www.optics.org, December 16, 2019.
  6. Phillip Sandborn, “FMCW Lidar: Scaling to the Chip-Level and Improving Phase-Noise-Limited Performance”, Electrical Engineering and Computer Sciences, University of California at Berkeley, Technical Report No. UCB/EECS-2019–148, December 1, 2019.
  7. “Technology readiness level”, Wikipedia
  8. A Gschwendtner, W Keicher, “Development of Coherent Laser Radar at Lincoln Laboratory”, MIT Tech journal, Vol 12, #2, 2000.
  9. C. Patel, “Stability of Single Frequency Lasers”, IEEE J Quantum Electronics, v4, 1968.
  10. Voxtel Laser Rangefinders, www.voxtel-inc.com, June 2020
  11. P Suni et al, “Photonic Integrated Circuit FMCW Lidar On A Chip”, 19th Coherent Laser Radar Conference

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For Data sensing and AI Infrastructure
For Data sensing and AI Infrastructure

Written by For Data sensing and AI Infrastructure

Marc. Y. , Product and R&D Director. Focus on Data Sensing and AI Infrastructure. More info at http://4da.tech.

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