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Open AccessArticle

An Improved ACKF/KF Initial Alignment Method for Odometer-Aided Strapdown Inertial Navigation System

1
Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150080, China
2
HIT (Anshan) Institute of Industrial Technology, Anshan 114000, China
*
Authors to whom correspondence should be addressed.
Sensors 2018, 18(11), 3896; https://doi.org/10.3390/s18113896
Received: 21 October 2018 / Revised: 1 November 2018 / Accepted: 11 November 2018 / Published: 12 November 2018
(This article belongs to the Special Issue Gyroscopes and Accelerometers)
For a land-vehicle strapdown inertial navigation system (SINS), the problem of initial alignment with large misalignment angle in-motion needs to be solved urgently. This paper proposes an improved ACKF/KF initial alignment method for SINS aided by odometer. The SINS error equation with large misalignment angle is established first in the form of an Euler angle. The odometer/gyroscope dead reckoning (DR) error equation is deduced, which makes the observation equation linear when the position is taken as the observation of the Kalman filter. Then, based on the cubature Kalman filter, the Sage-Husa adaptive filter and the characteristics of the observation equation, an improved ACKF/KF method is proposed, which can accomplish initial alignment well in the case of unknown measurement noise. Computer simulation results show that the performance of the proposed ACKF/KF algorithm is superior to EKF, CKF and AEKF method in accuracy and stability, and the vehicle test validates its advantages. View Full-Text
Keywords: strapdown inertial navigation system (SINS); initial alignment; odometer; Sage-Husa adaptive filter; cubature Kalman filter (CKF) strapdown inertial navigation system (SINS); initial alignment; odometer; Sage-Husa adaptive filter; cubature Kalman filter (CKF)
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Gao, K.; Ren, S.; Yi, G.; Zhong, J.; Wang, Z. An Improved ACKF/KF Initial Alignment Method for Odometer-Aided Strapdown Inertial Navigation System. Sensors 2018, 18, 3896.

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