Research on Compensation Approach for Motion Error of Rotating Accelerometer Gravity Gradiometer

The rotating accelerometer gravity gradiometer (RAGG) is a gravity gradient measuring instrument designed for moving bases, and as such, the primary technical challenge in RAGG development lies in compensating for motion error. Nevertheless, the existing open research is limited in number and exhibits several limitations: a lack of systematic design for monitoring systems, inadequate model interpretability, missing parameters, and lack of experimental validation, among others. To address these issues, this article proposes a novel approach for compensating RAGG motion error, which encompasses two key contributions: 1) development of a multiparameter compensation model for RAGG motion errors based on the motion transfer mechanism and accelerometer output model; and 2) by leveraging RAGG’s internal accelerometers, only four external sensors are utilized to achieve six-degree-of-freedom motion monitoring, thereby streamlining the motion monitoring system. Furthermore, a six-degree-of-freedom movement platform is utilized to construct an experimental test platform, validating the method’s effectiveness and practical applicability through real experiments. The proposed method is also subjected to comparative experimentation with existing approaches. The experimental results demonstrate that the method presented in this study exhibits superior performance, achieving over three orders of magnitude of compensation capability within the 0.35–0.65-Hz bandwidth, and attaining a motion error compensation level of 99.91%.

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Publication Details

Journal
IEEE Transactions on Instrumentation and Measurement
Published
2025-01-01
DOI
https://doi.org/10.1109/tim.2025.3556194
Citations
1
Primary Topic
Inertial Sensor and Navigation
Type
article
Field-Weighted Citation Impact
4.99
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article

Research on Compensation Approach for Motion Error of Rotating Accelerometer Gravity Gradiometer

Mingbiao Yu, Zebing Zhou, Li Yu, Ji Fan et al.
1 citations
IEEE Transactions on Instrumentation and Measurement
Inertial Sensor and Navigation
4.99
article

Research on Compensation Approach for Motion Error of Rotating Accelerometer Gravity Gradiometer

Mingbiao Yu, Zebing Zhou, Li Yu, Ji Fan, Liangcheng Tu, Chenyuan Hu, Tao Jiang, Xiaobing Yu, Huafeng Liu, Yu Liang, Bohai Ke
article en
1 citations

Abstract

The rotating accelerometer gravity gradiometer (RAGG) is a gravity gradient measuring instrument designed for moving bases, and as such, the primary technical challenge in RAGG development lies in compensating for motion error. Nevertheless, the existing open research is limited in number and exhibits several limitations: a lack of systematic design for monitoring systems, inadequate model interpretability, missing parameters, and lack of experimental validation, among others. To address these issues, this article proposes a novel approach for compensating RAGG motion error, which encompasses two key contributions: 1) development of a multiparameter compensation model for RAGG motion errors based on the motion transfer mechanism and accelerometer output model; and 2) by leveraging RAGG’s internal accelerometers, only four external sensors are utilized to achieve six-degree-of-freedom motion monitoring, thereby streamlining the motion monitoring system. Furthermore, a six-degree-of-freedom movement platform is utilized to construct an experimental test platform, validating the method’s effectiveness and practical applicability through real experiments. The proposed method is also subjected to comparative experimentation with existing approaches. The experimental results demonstrate that the method presented in this study exhibits superior performance, achieving over three orders of magnitude of compensation capability within the 0.35–0.65-Hz bandwidth, and attaining a motion error compensation level of 99.91%.

IEEE Transactions on Instrumentation and MeasurementVol. 74
Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 7%
Inertial Sensor and Navigation
4.99
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