Multi-Depth Sensing for Applications with Indirect Solid-State LiDAR

Armin Schonlieb, David Lugitsch, Christian Steger, Gerald Holweg, Norbert Druml

Publikation: KonferenzbeitragPaper

Abstract

In recent years, topics like autonomous driving increased the demand on robust environmental sensors. Depth sensors are most commonly used. Solid state Light Detection And Ranging (LiDAR) sensors are well suited for these applications. The measurement principle is based on measuring the phase and consequently the delay of emitted and reflected light. Problems arise if strong reflectors, like street-signs, impair the measurement. In this paper, we present a novel algorithm for depth calculation, based on indirect Time-of-Flight (ToF) data. With this approach it is possible to separate multiple reflectors in the scenery. This allows the generation of multiple depth images. In our approach an arbitrary number of different code sequences are applied as modulation signal. With these code sequences we generate a so called ToF-matrix. With this ToFmatrix, the measured environmental response can be mapped to a distance. As our evaluation shows, our method is able to achieve results with more information compared to conventional ToF-imaging. We demonstrate the separation of the reflection of a street-sign, from a target. This algorithm enables the usage of indirect ToF in automotive areas. We believe that this versatile calculation approach can increase the benefit of indirect LiDAR application for autonomous driving.

Originalspracheenglisch
Seiten919-925
Seitenumfang7
DOIs
PublikationsstatusVeröffentlicht - 8 Jan 2021
Veranstaltung31st IEEE Intelligent Vehicles Symposium, IV 2020 - Virtual, Las Vegas, USA / Vereinigte Staaten
Dauer: 19 Okt 202013 Nov 2020

Konferenz

Konferenz31st IEEE Intelligent Vehicles Symposium, IV 2020
LandUSA / Vereinigte Staaten
OrtVirtual, Las Vegas
Zeitraum19/10/2013/11/20

ASJC Scopus subject areas

  • !!Computer Science Applications
  • Fahrzeugbau
  • !!Modelling and Simulation

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