Advances in Single-Photon Lidar for Autonomous Vehicles: Working Principles, Challenges, and Recent Advances

Joshua Rapp*, Julián Tachella, Yoann Altmann, Stephen McLaughlin, Vivek K. Goyal

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

91 Citations (Scopus)
1310 Downloads (Pure)

Abstract

The safety and success of autonomous vehicles (AVs) depend on their ability to accurately map and respond to their surroundings in real time. One of the most promising recent technologies for depth mapping is single-photon lidar (SPL), which measures the time of flight of individual photons. The long-range capabilities (kilometers), excellent depth resolution (centimeters), and use of low-power (eye-safe) laser sources renders this modality a strong candidate for use in AVs. While presenting unique opportunities, the remarkable sensitivity of single-photon detectors introduces several signal processing challenges. The discrete nature of photon counting and the particular design of the detection devices means the acquired signals cannot be treated as arising in a linear system with additive Gaussian noise. Moreover, the number of useful photon detections may be small despite a large data volume, thus requiring careful modeling and algorithmic design for real-time performance. This article discusses the main working principles of SPL and summarizes recent advances in signal processing techniques for this modality, highlighting promising applications in AVs as well as a number of challenges for vehicular lidar that cannot be solved by better hardware alone.

Original languageEnglish
Pages (from-to)62-71
Number of pages10
JournalIEEE Signal Processing Magazine
Volume37
Issue number4
Early online date29 Jun 2020
DOIs
Publication statusPublished - Jul 2020

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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