Extraction of precise object orientation and position from LIDAR data using maximum-likelihood methods

Esen Salcin, Andres Diaz, Travis Sawyer, Jonathan S. Friedman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

LIDAR-based measurement systems can overcome several limitations in comparable technologies for the measurement and mapping of 3D static and dynamic objects in any given reference frame. As a result, they present distinct advantages for the determination of target velocity, acceleration, roll, pitch, yaw and position from long distances. Continuous, precise sensing and monitoring of remote targets has applications in various areas including military and commercial systems from ground, air or space. In this manuscript, we present the use of Maximum-Likelihood Estimation (MLE) methods for the extraction of precise object orientation and position information from a "waveform-sensing"LIDAR detector, where the finely-sampled (> GHz) temporal waveform of the signal generated by the diffuse-reflected laser pulse (i.e., laser pulse reflected off of the object and returned to collection optics) is used. In this method, multiple waveforms generated by the return pulse from various detectors stationed at optimized specific positions are collected. The time-of-flight (TOF), shape and the duration of waveforms indicate the radial extent of the object and distance to the receiver. Position and orientation are then extracted from the waveforms using MLE. First, we describe the forward-model simulation tool to generate LIDAR waveform data for an arbitrary object position and orientation. Next, we present a brief introduction into MLE followed by the application of this method to the extraction of position and orientation parameters from the simulated LIDAR data. Finally, results are presented to demonstrate the accuracy of the proposed method in recovering the input object orientation and position under presence of noise.

Original languageEnglish (US)
Title of host publicationLaser Radar Technology and Applications XXVI
EditorsMonte D. Turner, Gary W. Kamerman
PublisherSPIE
ISBN (Electronic)9781510643253
DOIs
StatePublished - 2021
Externally publishedYes
EventLaser Radar Technology and Applications XXVI 2021 - Virtual, Online, United States
Duration: Apr 12 2021Apr 16 2021

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11744
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceLaser Radar Technology and Applications XXVI 2021
Country/TerritoryUnited States
CityVirtual, Online
Period4/12/214/16/21

Keywords

  • 3D remote sensing
  • LADAR
  • LIDAR
  • Maximum likelihood estimation
  • attitude
  • direct detection
  • tracking

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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