Observability Analysis and Optimization of Cooperative Navigation System With a Low-Cost Inertial Sensor Array

Shen, Kai; Zuo, Jianwen; Li, Yuelun; Zuo, Siqi; Guo, Wenjun

doi:10.1109/jiot.2023.3235524

Cited by 8 publications

(1 citation statement)

References 30 publications

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“…According to the model, a Kalman filter is used for data fusion. The system noise matrix and measurement noise matrix in the Kalman filter are set according to the noise parameters obtained by Allan variance [20][21][22][23], as shown in Figure 5 below: The output error model of the MEMS gyroscope is shown as follows [24][25][26][27]:…”

Section: Data Fusion Of Redundant Mems-imumentioning

confidence: 99%

Redundant Configuration Method of MEMS Sensors for Bottom Hole Assembly Attitude Measurement

Zheng,

Wang,

Zhang

et al. 2024

Micromachines

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Micro-electro-mechanical systems inertial measurement units (MEMS-IMUs) are increasingly being employed for measuring the attitude of bottom hole assemblies (BHAs). However, the reliability and measurement precision of a single MEMS-IMU may not meet drilling’s stringent needs. Redundant MEMS-IMU systems can effectively enhance the reliability and precision. This paper proposes a redundant configuration method for MEMS sensors tailored to BHA attitude measurement. Firstly, based on reliability theory and a cost-benefit analysis, considering factors such as cost, size, and reliability, the optimal number of sensors in the redundant system was determined to be six. Considering the structural characteristics of the BHA, a hollow hexagonal prism-shaped redundant configuration scheme was proposed, ensuring the circulation of drilling fluid within the drill pipe. Next, by employing Kalman filtering to integrate the output data from the six sensors, a virtual IMU (VIMU) was formed. Finally, experimental verification was carried out. The results confirmed that, after redundancy implementation, the velocity random walk of the accelerometer decreased by an average of 58% compared to a single MEMS-IMU, and bias instability was reduced by an average of 54%. The angular random walk of the gyroscope decreased by an average of 58%, and bias instability was reduced by an average of 37%. This research provides a theoretical foundation for enhancing the precision and reliability of BHA attitude measurements.

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