Version 1
: Received: 16 October 2017 / Approved: 16 October 2017 / Online: 16 October 2017 (06:35:24 CEST)
How to cite:
Wang, M.; He, X.; Wu, W.; Liu, Z. A Study on Minimum Sigma Set SRUKF Based GPS/INS Tightly-Coupled System. Preprints2017, 2017100103. https://doi.org/10.20944/preprints201710.0103.v1
Wang, M.; He, X.; Wu, W.; Liu, Z. A Study on Minimum Sigma Set SRUKF Based GPS/INS Tightly-Coupled System. Preprints 2017, 2017100103. https://doi.org/10.20944/preprints201710.0103.v1
Wang, M.; He, X.; Wu, W.; Liu, Z. A Study on Minimum Sigma Set SRUKF Based GPS/INS Tightly-Coupled System. Preprints2017, 2017100103. https://doi.org/10.20944/preprints201710.0103.v1
APA Style
Wang, M., He, X., Wu, W., & Liu, Z. (2017). A Study on Minimum Sigma Set SRUKF Based GPS/INS Tightly-Coupled System. Preprints. https://doi.org/10.20944/preprints201710.0103.v1
Chicago/Turabian Style
Wang, M., Wenqi Wu and Zhenbo Liu. 2017 "A Study on Minimum Sigma Set SRUKF Based GPS/INS Tightly-Coupled System" Preprints. https://doi.org/10.20944/preprints201710.0103.v1
Abstract
In this paper, firstly, some questionable formulas and conceptual oversights of previous reduced sigma set unscented transformation (UT) methods are revised through theoretical analysis. Then the revised UT methods based Kalman filters are used in a GPS/INS tightly-coupled system. The Kalman filter flows are the kind of square-root, since the square-root unscented Kalman filters (SRUKFs) can guarantee the stability of the system. By using the reduced sigma set SRUKFs (which contain simplex sigma set square-root unscented Kalman filter (S-SRUKF), spherical simplex sigma set square-root unscented Kalman filter (SS-SRUKF) and minimum sigma set square-root unscented Kalman filter (M-SRUKF)), the computation cost is greatly saved compared with the standard SRUKF, while the accuracy of the GPS/INS tightly-coupled system still maintained. The structure of the GPS/INS tightly-coupled system is in the form of error state, and the time updates of the state and the state covariance of SRUKFs are directly estimated without using UT, thus the computational time is also greatly saved. The pseudo-satellite is introduced to aid the system when the observation information is deficient, for example, when the GPS signal is deficient in the maneuver environment. By using the pseudo-satellite, the optimal performance of the system is guaranteed. Experiment of unmanned aerial vehicle (UAV) showed that the pseudo-satellite aided mechanism worked well.
Keywords
reduced sigma set Square-Root Unscented Kalman Filter; pseudo-satellite; UAV; GPS/INS tightly-coupled system
Subject
Computer Science and Mathematics, Information Systems
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.
