Coarse Alignment of Strapdown Inertial Navigation System Based on LMS Adaptive Filtering

Zhu, Yuxuan; Qiao, Pengchao

doi:10.1109/icivc47709.2019.8980991

Cited by 1 publication

(2 citation statements)

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“…Currently, the coarse alignment methods for SINS on a swing base can be divided into two categories: one category is to directly determine the initial attitude matrix through the gravity vectors of two or more moments by the TRIAD algorithm [ 8 , 9 , 10 , 11 , 12 ]. In [ 8 ], the initial rotation matrix is decomposed by attitude matrix decomposition to isolate the influence of the swing base and estimate the rotation matrix by two noncollinear gravity vectors.…”

Section: Introductionmentioning

confidence: 99%

“…On this basis, [ 9 , 10 , 11 ] one can reduce the impact of the inertial measurement unit (IMU) output noise on the estimation results by adding a low-pass filter. Different from other studies [ 9 , 10 , 11 ], the authors of [ 12 ] used an LMS adaptive filter to reduce sensor noise, and the authors of [ 13 ] computed two initial rotation matrices using the gravity vectors from multiple moments and weighted averaged according to the standard deviation observed at each time, which improves the alignment accuracy. In an earlier study [ 14 ], to extract the effective observation vectors from the inertial sensors’ outputs, a method for parameter recognition and vector reconstruction was designed, where an adaptive Kalman filter was employed to estimate the unknown parameters.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Coarse Alignment Method for SINS Using Special Orthogonal Group Optimal Estimation

Pei

Yang

Zhu

et al. 2020

Sensors

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Aimed at the alignment problem of strapdown inertial navigation system (SINS) on the swing base, a novel coarse alignment method using special orthogonal group optimal estimation is proposed. There are two main contributions in this paper. First, based on the Lie group differential equation, the rotation matrix is updated directly by using error Lie algebra, which avoids the non-convexity of traditional methods and the need for non-collinear vector observation. Second is that a novel optimal estimation method is developed by using the exact error Lie algebra, which is calculated based on the physical definition of Lie algebra, as the innovation term to compensate the initial special orthogonal group in the estimation process. The asymptotic convergence of the proposed optimal estimation method is proved by Lyapunov's second law. The simulation and experimental results demonstrate that the proposed method exhibits better performance than existing methods in alignment accuracy and time, which can achieve the self-alignment of SINS on the swing base.

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