Version 1
: Received: 8 January 2018 / Approved: 9 January 2018 / Online: 9 January 2018 (07:47:45 CET)
How to cite:
García, J.; Molina, J.M.; Trincado, J. A Methodology for Design and Analysis of Sensor Fusion with Real Data in UAV Platforms. Preprints2018, 2018010077. https://doi.org/10.20944/preprints201801.0077.v1
García, J.; Molina, J.M.; Trincado, J. A Methodology for Design and Analysis of Sensor Fusion with Real Data in UAV Platforms. Preprints 2018, 2018010077. https://doi.org/10.20944/preprints201801.0077.v1
García, J.; Molina, J.M.; Trincado, J. A Methodology for Design and Analysis of Sensor Fusion with Real Data in UAV Platforms. Preprints2018, 2018010077. https://doi.org/10.20944/preprints201801.0077.v1
APA Style
García, J., Molina, J.M., & Trincado, J. (2018). A Methodology for Design and Analysis of Sensor Fusion with Real Data in UAV Platforms. Preprints. https://doi.org/10.20944/preprints201801.0077.v1
Chicago/Turabian Style
García, J., Jose Manuel Molina and Jorge Trincado. 2018 "A Methodology for Design and Analysis of Sensor Fusion with Real Data in UAV Platforms" Preprints. https://doi.org/10.20944/preprints201801.0077.v1
Abstract
This paper presents a methodology to design sensor fusion parameters using real performance indicators of navigation in UAVs based on PixHawk flight controller and peripherals. This methodology and the selected performance indicators allows to find the best parameters for the fusion system of a determined configuration of sensors and a predefined real mission. The selected real platform is described with stress on available sensors and data processing software, and the experimental methodology is proposed to characterize sensor data fusion output and determine the best choice of parameters using quality measurements of tracking output with performance metrics not requiring ground truth.
Keywords
UAVs sensor fusion; EKF; real data analysis; system design
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
