Digital-Twin-Assisted Fault Diagnosis for IMU in Rotational Inertial Navigation Systems

作者：H. N. Li, Gongliu Yang, Qingzhong Cai, Yongqiang Tu · 发表于：IEEE Sensors Journal · 年份：2025 · DOI：10.1109/jsen.2025.3634111 · 被引用次数：1 · 研究领域：Inertial Sensor and Navigation、GNSS positioning and interference、Space Satellite Systems and Control

The rotational inertial navigation systems (RINS) is a type of inertial system designed for high-precision and long-duration navigation tasks. As a core component of inertial navigation systems, the inertial measurement unit (IMU) plays a critical role, and its malfunction can significantly degrade the accuracy of long-duration navigation results due to the cumulative nature of inertial integration. The introduction of the rotary mechanism in RINS enables rotational modulation, which effectively enhances long-term accuracy. However, this rotational modulation also introduces new challenges for IMU fault diagnosis. Therefore, researching IMU fault diagnosis tailored to the characteristics of RINS is of great significance for ensuring the long-term accuracy and reliability of the system. In this paper, a digital-twin-assisted IMU fault diagnosis method is proposed for RINS. Under static conditions, the proposed method achieves an overall fault classification accuracy of 97.99%, representing an average improvement of 28.04% over conventional data-driven approaches. In tests conducted under harsh vehicle conditions, the method attains a fault classification accuracy of 84.27%, which is about 25.08% average higher than that of data-driven methods. These results demonstrate the feasibility and effectiveness of the proposed approach.