Document Type
Article
Publication Date
2018
College/Unit
Statler College of Engineering and Mining Resources
Department/Program/Center
Mechanical and Aerospace Engineering
Abstract
We present various performance trades for multiantenna global navigation satellite system (GNSS) multisensor attitude estimation systems. In particular, attitude estimation performance sensitivity to various error sources and system configurations is assessed. This study is motivated by the need for system designers, scientists, and engineers of airborne astronomical and remote sensing platforms to better determine which system configuration is most suitable for their specific application. In order to assess performance trade-offs, the attitude estimation performance of various approaches is tested using a simulation that is based on a stratospheric balloon platform. For GNSS errors, attention is focused on multipath, receiver measurement noise, and carrier- phase breaks. For the remaining attitude sensors, different performance grades of sensors are assessed. Through a Monte Carlo simulation, it is shown that, under typical conditions, sub-0.1-degree attitude accuracy is available when using multiple antenna GNSS data only, but that this accuracy can degrade to degree level in some environments warranting the inclusion of additional attitude sensors to maintain the desired level of accuracy. Further, we show that integrating inertial sensors is more valuable whenever accurate pitch and roll estimates are critical.
Digital Commons Citation
Tehrani, Nathan A. and Gross, Jason N., "Performance Trades for Multiantenna GNSS Multisensor Attitude Determination Systems" (2018). Faculty & Staff Scholarship. 2088.
https://researchrepository.wvu.edu/faculty_publications/2088
Source Citation
Tehrani, N. A., & Gross, J. N. (2018). Performance Trades for Multiantenna GNSS Multisensor Attitude Determination Systems. International Journal of Aerospace Engineering, 2018, 1–12. https://doi.org/10.1155/2018/4871239
Comments
Copyright © 2018 Nathan A. Tehrani and Jason N. Gross. 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.