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Open AccessArticle

A Combined Gravity Compensation Method for INS Using the Simplified Gravity Model and Gravity Database

by Xiao Zhou 1,2,*, Gongliu Yang 1,2, Jing Wang 3 and Zeyang Wen 1,2
1
School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing 100191, China
2
Science and Technology on Inertial Laboratory, Beihang University, Beijing 100191, China
3
School of Mechatronices and Information Engineering, China Mining University, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(5), 1552; https://doi.org/10.3390/s18051552
Received: 21 March 2018 / Revised: 29 April 2018 / Accepted: 8 May 2018 / Published: 14 May 2018
(This article belongs to the Section Physical Sensors)
In recent decades, gravity compensation has become an important way to reduce the position error of an inertial navigation system (INS), especially for a high-precision INS, because of the extensive application of high precision inertial sensors (accelerometers and gyros). This paper first deducts the INS’s solution error considering gravity disturbance and simulates the results. Meanwhile, this paper proposes a combined gravity compensation method using a simplified gravity model and gravity database. This new combined method consists of two steps all together. Step 1 subtracts the normal gravity using a simplified gravity model. Step 2 first obtains the gravity disturbance on the trajectory of the carrier with the help of ELM training based on the measured gravity data (provided by Institute of Geodesy and Geophysics; Chinese Academy of sciences), and then compensates it into the error equations of the INS, considering the gravity disturbance, to further improve the navigation accuracy. The effectiveness and feasibility of this new gravity compensation method for the INS are verified through vehicle tests in two different regions; one is in flat terrain with mild gravity variation and the other is in complex terrain with fierce gravity variation. During 2 h vehicle tests, the positioning accuracy of two tests can improve by 20% and 38% respectively, after the gravity is compensated by the proposed method. View Full-Text
Keywords: error modelling; gravity model; extreme learning machine (ELM); gravity compensation; high precision free-INS error modelling; gravity model; extreme learning machine (ELM); gravity compensation; high precision free-INS
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Zhou, X.; Yang, G.; Wang, J.; Wen, Z. A Combined Gravity Compensation Method for INS Using the Simplified Gravity Model and Gravity Database. Sensors 2018, 18, 1552.

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