Author:
Liang Siyuan,Dong Xiaochao,Guo Tianyu,Zhao Feng,Zhang Yuhua
Abstract
The MEMS array-based inertial navigation module (M-IMU) reduces the measurement singularities of MEMS sensors by fusing multiple data processing to improve its navigation performance. However, there are still existing random and fixed errors in M-IMU navigation. The calibration method calibrates the fixed error parameters of M-IMU to further improve navigation accuracy. In this paper, we propose a low-cost and efficient calibration method to effectively estimate the fixed error parameters of M-IMU. Firstly, we manually rotate the M-IMU in multiple sets of different attitudes (stationary), then use the LM-calibration algorithm to optimize the cost function of the corresponding sensors in different intervals of the stationary-dynamic filter separation to obtain the fixed error parameters of MEMS, and finally, the global fixed error parameters of the M-IMU are calibrated by adaptive support fusion of the individual MEMS fixed error parameters based on the benchmark conversion. A comparison of the MEMS calibrated separately by the fusion-calibration algorithm and the LM-calibration algorithm verified that the calibrated MEMS array improved the measurement accuracy by about 10 db and reduced the dispersion of the output data by about 8 db compared to the individual MEMS in a multi-dimensional test environment, indicating the robustness and feasibility of the fusion calibration algorithm.
Funder
Science and Technology Department of Shaanxi Province
Subject
Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering
Cited by
1 articles.
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