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Comparison of MEMS-based and FOG-based IMUs to determine sensor pose on an unmanned aircraft system

Citation

Gautam, D and Lucieer, A and Malenovsky, Z and Watson, C, Comparison of MEMS-based and FOG-based IMUs to determine sensor pose on an unmanned aircraft system, Journal of Surveying Engineering, 143, (4) Article 04017009. ISSN 0733-9453 (2017) [Refereed Article]

Copyright Statement

2017 ASCE

DOI: doi:10.1061/(ASCE)SU.1943-5428.0000225

Abstract

Small-sized unmanned aircraft systems (UAS) are restricted to use only lightweight microelectromechanical systems (MEMS)- based inertial measurement units (IMUs) due to their limited payload capacity. Still, some UAS-based geospatial remote sensing applications, such as airborne spectroscopy or laser scanning, require high accuracy pose (position and orientation) determination of the onboard sensor payload. This study presents ground-based experiments investigating the pose accuracy of two MEMS-based IMUs: the single-antennaMTi-G-700 (Xsens, Enschede, Netherlands) and the dual-antenna/dual-frequency Spatial Dual IMU (Advanced Navigation, Sydney, Australia)/global navigation satellite system (GNSS).A tightly coupled and postprocessed pose solution froma fiberoptic gyroscope (FOG)-based NovAtel synchronized position attitude navigation (SPAN) IMU (NovAtel, Calgary, Canada) served as a reference to evaluate the performance of the two IMUs under investigation. Results revealed a better position solution for the Spatial Dual, and the MTi-G-700 achieved a better roll/pitch accuracy. Most importantly, the heading solution from the dual-antenna configuration of the Spatial Dual was found to be more stable than the heading obtained with the reference SPANIMU.

Item Details

Item Type:Refereed Article
Keywords:unmanned aircraft systems (UAS), fiberoptic gyroscope (FOG), microelectromechanical systems (MEMS), inertial measurement units (IMUs), global navigation satellite system (GNSS), accuracy, pose
Research Division:Agricultural and Veterinary Sciences
Research Group:Crop and Pasture Production
Research Field:Crop and Pasture Biochemistry and Physiology
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management of Farmland, Arable Cropland and Permanent Cropland Environments
Author:Gautam, D (Mr Deepak Gautam)
Author:Lucieer, A (Associate Professor Arko Lucieer)
Author:Watson, C (Dr Christopher Watson)
ID Code:117641
Year Published:2017
Funding Support:Australian Research Council (DP140101488)
Web of Science® Times Cited:1
Deposited By:Geography and Spatial Science
Deposited On:2017-06-22
Last Modified:2018-05-21
Downloads:0

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