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Sensors 2016, 16(6), 940;

Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units

School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing 100191, China
Space Star Technology Co., Ltd., Beijing 100101, China
Author to whom correspondence should be addressed.
Academic Editor: Jörg F. Wagner
Received: 7 April 2016 / Revised: 26 May 2016 / Accepted: 15 June 2016 / Published: 22 June 2016
(This article belongs to the Special Issue Inertial Sensors and Systems 2016)
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An inertial navigation system (INS) has been widely used in challenging GPS environments. With the rapid development of modern physics, an atomic gyroscope will come into use in the near future with a predicted accuracy of 5 × 10−6°/h or better. However, existing calibration methods and devices can not satisfy the accuracy requirements of future ultra-high accuracy inertial sensors. In this paper, an improved calibration model is established by introducing gyro g-sensitivity errors, accelerometer cross-coupling errors and lever arm errors. A systematic calibration method is proposed based on a 51-state Kalman filter and smoother. Simulation results show that the proposed calibration method can realize the estimation of all the parameters using a common dual-axis turntable. Laboratory and sailing tests prove that the position accuracy in a five-day inertial navigation can be improved about 8% by the proposed calibration method. The accuracy can be improved at least 20% when the position accuracy of the atomic gyro INS can reach a level of 0.1 nautical miles/5 d. Compared with the existing calibration methods, the proposed method, with more error sources and high order small error parameters calibrated for ultra-high accuracy inertial measurement units (IMUs) using common turntables, has a great application potential in future atomic gyro INSs. View Full-Text
Keywords: systematic calibration; ultrahigh-accuracy inertial measurement unit; error modelling; Kalman filter systematic calibration; ultrahigh-accuracy inertial measurement unit; error modelling; Kalman filter

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Cai, Q.; Yang, G.; Song, N.; Liu, Y. Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units. Sensors 2016, 16, 940.

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