Attitude and Heading Calibration After IMU Reinstallation in Rotational Inertial Navigation Systems Using an Interleaved Rotation-Dwell Sequence

To address the degradation in attitude accuracy caused by mismatched rotation-axis tilt parameters after inertial measurement unit (IMU) reinstallation in rotational inertial navigation systems (RINSs) on large marine platforms, an interleaved rotation-dwell attitude-and-heading calibration method is proposed. First, a relative attitude-and-heading model incorporating the combined effects of the rotation-axis tilt errors of the two systems is established, with the horizontal error mapping induced by the relative heading between their base frames explicitly considered. Second, a four-state interleaved rotation-dwell sequence is designed, and the rotation-axis tilt parameters of the two RINSs are separated in closed form through Hadamard orthogonal projection. Simulations verify the parameter-decoupling capability of the proposed method. Experimental results show that, compared to a filtering-based self-calibration method for a single RINS, the proposed method reduces the roll and pitch root-mean-square errors (RMSE) by 90.29% and 41.80%, respectively. After compensation for the rotation-axis tilt errors, relative heading alignment between the two systems is achieved by estimating the residual heading bias. The proposed method provides a system-level solution for attitude-and-heading calibration after IMU reinstallation under moving-base field conditions.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2026-08-17
DOI
https://doi.org/10.3390/jmse14161525
Primary Topic
Inertial Sensor and Navigation
Type
article
Field-Weighted Citation Impact
0.00

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article

Attitude and Heading Calibration After IMU Reinstallation in Rotational Inertial Navigation Systems Using an Interleaved Rotation-Dwell Sequence

Feng Zha, Hongyang He, Haoyu Bu, Chenyang Zhang et al.
Journal of Marine Science and Engineering
Inertial Sensor and Navigation
article

Attitude and Heading Calibration After IMU Reinstallation in Rotational Inertial Navigation Systems Using an Interleaved Rotation-Dwell Sequence

Feng Zha, Hongyang He, Haoyu Bu, Chenyang Zhang, Jingshu Li, Qun Zheng
article en

Abstract

To address the degradation in attitude accuracy caused by mismatched rotation-axis tilt parameters after inertial measurement unit (IMU) reinstallation in rotational inertial navigation systems (RINSs) on large marine platforms, an interleaved rotation-dwell attitude-and-heading calibration method is proposed. First, a relative attitude-and-heading model incorporating the combined effects of the rotation-axis tilt errors of the two systems is established, with the horizontal error mapping induced by the relative heading between their base frames explicitly considered. Second, a four-state interleaved rotation-dwell sequence is designed, and the rotation-axis tilt parameters of the two RINSs are separated in closed form through Hadamard orthogonal projection. Simulations verify the parameter-decoupling capability of the proposed method. Experimental results show that, compared to a filtering-based self-calibration method for a single RINS, the proposed method reduces the roll and pitch root-mean-square errors (RMSE) by 90.29% and 41.80%, respectively. After compensation for the rotation-axis tilt errors, relative heading alignment between the two systems is achieved by estimating the residual heading bias. The proposed method provides a system-level solution for attitude-and-heading calibration after IMU reinstallation under moving-base field conditions.

Journal of Marine Science and EngineeringVol. 14(16)
Naval University of Engineering (CN)
National Natural Science Foundation of China
Life below water
Openalex Percentile: Top 6%
Inertial Sensor and Navigation
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Attitude and Heading Calibration After IMU Reinstallation in Rotational Inertial Navigation Systems Using an Interleaved Rotation-Dwell Sequence — Feng Zha, Hongyang He, et al. · Journal of Marine Science and Engineering (2026) | TGRS Research Map | TGRS