• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Scopus
  4. Extended Target Tracking with a Lidar Sensor Using Random Matrices and a Gaussian Processes Regression Model
 
  • Details
  • Full
Options
2023
Conference Paper
Title

Extended Target Tracking with a Lidar Sensor Using Random Matrices and a Gaussian Processes Regression Model

Abstract
Random matrices are used to filter the center of gravity (CoG) and the covariance matrix of measurements. However, these quantities do not always correspond directly to the position and the extent of the object, e.g. when a lidar sensor is used.In this paper, we propose a Gaussian processes regression model (GPRM) to predict the position and extension of the object from the filtered CoG and covariance matrix of the measurements. Training data for the GPRM are generated by a sampling method and a virtual measurement model (VMM). The VMM is a function that generates artificial measurements using ray tracing and allows us to obtain the CoG and covariance matrix that any object would cause. This enables the GPRM to be trained without real data but still be applied to real data due to the precise modeling in the VMM. The results show an accurate extension estimation as long as the reality behaves like the modeling and e.g. lidar measurements only occur on the side facing the sensor.
Author(s)
Hoher, Patrick
Hochschule Konstanz University of Applied Sciences
Reuter, Johannes
Hochschule Konstanz University of Applied Sciences
Dold, Daniel
Hochschule Konstanz University of Applied Sciences
Griesser, Dennis
Hochschule Konstanz University of Applied Sciences
Govaers, Felix  
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Koch, Wolfgang
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Mainwork
26th International Conference on Information Fusion, FUSION 2023  
Conference
International Conference on Information Fusion 2023  
DOI
10.23919/FUSION52260.2023.10224159
Language
English
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Keyword(s)
  • Extended object tracking

  • extension estimation

  • Gaussian processes

  • lidar

  • random matrices

  • reference model

  • regression

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024