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A Factor Graph Optimization Method With Initial Velocity Bias Estimation for GINS Initial Alignment

delete2026-08-12
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PRE
AI
X
Xiaoren Zhou
M
Meng Zhang
C
Chengshuai Wu
J
Jianchen Hu
X
Xiaohong Guan
DOI:10.1109/tase.2026.3723023delete
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Abstract

Abstract

En 中文
Initial alignment is a crucial stage in navigation because it directly determines the navigation accuracy of the global positioning system (GPS)-inertial navigation system (GINS) that consists of the GPS and the strapdown inertial navigation system. However, GPS outliers and their resultant initial velocity bias error, both caused by the GPS signal blockage and/or reflection, severely degrade the GINS initial alignment accuracy. In addition, the inertial measurement unit (IMU) bias can also cause the cumulative bias error to adversely affect the alignment accuracy. In order to simultaneously suppress these errors for the GINS initial alignment, we propose a factor graph optimization (FGO) method that models the initial velocity bias as a state. Specifically, the IMU bias and the initial velocity bias are estimated and then compensated to improve the alignment accuracy. The Huber norm is employed to suppress the GPS outliers and thus the stable alignment process can be achieved. A global observability analysis is conducted, showing that the newly augmented initial velocity bias, together with the other estimated states, is observable when the vehicle trajectory contains a constant-attitude straight-line motion interval during which the specific-force derivative vectors at two distinct instants are linearly independent. The car-mounted experiment results demonstrate that the proposed FGO method can effectively suppress the aforementioned errors. Note to Practitioners—This article proposes a methodology for initial alignment of an IMU with GPS aided. In practice, when GPS outliers occur, the first GPS measurement may be contaminated to introduce an initial velocity bias that can continuously and considerably degrade the alignment accuracy. Consequently, this article focuses on coping with not only GPS outliers, but also the initial velocity bias. In addition, cumulative IMU bias errors are also considered and addressed. The proposed method is particularly suitable for practitioners seeking reliable IMU and GPS integrated navigation in scenarios where GPS outliers may arise.
Keywords:
Initial alignment
initial velocity bias
strapdown inertial navigation system
factor graph optimization

Journal

IEEE Transactions on Automation Science and Engineering cover
IEEE Transactions on Automation Science and Engineering
IF:
6.4
Papers:
4.9K
Citations:
1.6W

Organization

X
xi'an jiaotong university
Scholars:
9.1W
Papers: 6.6W
Citations: 75