COLLABORATIVE NAVIGATION SIMULATION TOOL USING KALMAN FILTER with IMPLICIT CONSTRAINTS

authored by: N. Garcia-Fernandez, H. Alkhatib, S. Schön
Abstract: Collaborative Positioning (CP) is a networked positioning technique in which different multi-sensor systems (nodes) enhance the accuracy and precision of these navigation solutions by performing measurements or by sharing information (links) between each other. The wide spectrum of available sensors that are used in these complex scenarios bring the necessity to analyze the sensibility of the system to different configurations in order to find optimal solutions. In this paper, we discuss the implementation and evaluation of a simulation tool that allows us to study these questions. The simulation tool is successfully implemented as a plane based localization problem, in which the sensor measurements are fused in a Collaborative Extended Kalman Filter (C-EKF) algorithm with implicit constraints. Using a real urban scenario with three vehicles equipped with various positioning sensors, the impact of the sensor configuration is investigated and discussed by intensive Monte Carlo simulations. The results show the influence of the laser scanner measurements on the accuracy and precision of the estimation, and the increased performance of the collaborative navigation techniques with respect to the single vehicle method.
Organisation(s): Institute of Geodesy
Geodetic Institute
Leibniz Research Centre FZ:GEO
Type: Conference article
Journal: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Volume: 4
Pages: 559-566
No. of pages: 8
ISSN: 2194-9042
Publication date: 29.05.2019
Publication status: E-pub ahead of print
Peer reviewed: Yes
ASJC Scopus subject areas: Earth and Planetary Sciences (miscellaneous), Environmental Science (miscellaneous), Instrumentation
Electronic version(s): https://doi.org/10.5194/isprs-annals-IV-2-W5-559-2019 (Access: Open)
https://doi.org/10.15488/10158 (Access: Open)
: Details in the research portal "Research@Leibniz University"

BibTeX

@article{3618d880bbec4c2f9b5498935f91f601,
title = "COLLABORATIVE NAVIGATION SIMULATION TOOL USING KALMAN FILTER with IMPLICIT CONSTRAINTS",
abstract = "Collaborative Positioning (CP) is a networked positioning technique in which different multi-sensor systems (nodes) enhance the accuracy and precision of these navigation solutions by performing measurements or by sharing information (links) between each other. The wide spectrum of available sensors that are used in these complex scenarios bring the necessity to analyze the sensibility of the system to different configurations in order to find optimal solutions. In this paper, we discuss the implementation and evaluation of a simulation tool that allows us to study these questions. The simulation tool is successfully implemented as a plane based localization problem, in which the sensor measurements are fused in a Collaborative Extended Kalman Filter (C-EKF) algorithm with implicit constraints. Using a real urban scenario with three vehicles equipped with various positioning sensors, the impact of the sensor configuration is investigated and discussed by intensive Monte Carlo simulations. The results show the influence of the laser scanner measurements on the accuracy and precision of the estimation, and the increased performance of the collaborative navigation techniques with respect to the single vehicle method.",
keywords = "Collaborative Navigation, Extended Kalman Filter (EKF), Monte Carlo Simulation, Multi-sensor fusion",
author = "N. Garcia-Fernandez and H. Alkhatib and S. Sch{\"o}n",
note = "Funding information: This work was supported by the German Research Foundation (DFG) as a part of the Research Training Group i.c.sens [GRK2159]. The computations were performed by the compute cluster, which is funded by the Leibniz Universit{\"a}t Hannover, the Lower Saxony Ministry of Science and Culture (MWK) and DFG.; 4th ISPRS Geospatial Week 2019 ; Conference date: 10-06-2019 Through 14-06-2019",
year = "2019",
month = may,
day = "29",
doi = "10.5194/isprs-annals-IV-2-W5-559-2019",
language = "English",
volume = "4",
pages = "559--566",
journal = "ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences",
issn = "2194-9042",
publisher = "Copernicus GmbH",
number = "2/W5",
}