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Funding
Funding for this research was provided by:
Shaanxi Provincial Science and Technology Department (2020JM-185)
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Article History
Accepted: 20 June 2024
First Online: 2 July 2024
Declarations
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: The authors have not disclosed any competing interests.
: This paper proposes an improved Kalman filtering algorithm (IAKF) based on initial alignment under shaking basis, which improves the alignment accuracy of standard Kalman filters under shaking basis.
