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Sensors (Basel). 2017 Jun 17;17(6). pii: E1424. doi: 10.3390/s17061424.

Coarse Alignment Technology on Moving base for SINS Based on the Improved Quaternion Filter Algorithm.

Zhang T1,2, Zhu Y3,4, Zhou F5,6, Yan Y7,8, Tong J9,10.

Author information

1
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. 101011356@seu.edu.cn.
2
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Nanjing 210096, China. 101011356@seu.edu.cn.
3
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. zhyy@seu.edu.cn.
4
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Nanjing 210096, China. zhyy@seu.edu.cn.
5
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. 220132619@seu.edu.cn.
6
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Nanjing 210096, China. 220132619@seu.edu.cn.
7
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. 220162808@seu.edu.cn.
8
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Nanjing 210096, China. 220162808@seu.edu.cn.
9
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. 230139522@seu.edu.cn.
10
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Nanjing 210096, China. 230139522@seu.edu.cn.

Abstract

Initial alignment of the strapdown inertial navigation system (SINS) is intended to determine the initial attitude matrix in a short time with certain accuracy. The alignment accuracy of the quaternion filter algorithm is remarkable, but the convergence rate is slow. To solve this problem, this paper proposes an improved quaternion filter algorithm for faster initial alignment based on the error model of the quaternion filter algorithm. The improved quaternion filter algorithm constructs the K matrix based on the principle of optimal quaternion algorithm, and rebuilds the measurement model by containing acceleration and velocity errors to make the convergence rate faster. A doppler velocity log (DVL) provides the reference velocity for the improved quaternion filter alignment algorithm. In order to demonstrate the performance of the improved quaternion filter algorithm in the field, a turntable experiment and a vehicle test are carried out. The results of the experiments show that the convergence rate of the proposed improved quaternion filter is faster than that of the tradition quaternion filter algorithm. In addition, the improved quaternion filter algorithm also demonstrates advantages in terms of correctness, effectiveness, and practicability.

KEYWORDS:

Doppler velocity log (DVL); coarse alignment; improved quaternion filter algorithm; strapdown inertial navigation system (SINS)

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