ITM Web Conf.
Volume 47, 20222022 2nd International Conference on Computer, Communication, Control, Automation and Robotics (CCCAR2022)
|Number of page(s)||8|
|Section||Algorithm Optimization and Application|
|Published online||23 June 2022|
Research on motion track error detection and compensation algorithm based on MEMS sensor
School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai, China
* Corresponding author: firstname.lastname@example.org
Due to various errors in actual use, MEMS inertial sensors have large errors in the detection of motion trajectories. Therefore, it is necessary to analyse and model the errors to decrease the impact of error sources on the detection system. This errors mainly include systematic random errors and accumulated errors generated during double integral operation, and different filtering methods are used for different types of errors. For random errors, the wavelet fuzzy threshold method is used to filter the sensor output signal. For the accumulated error, the zero-state adaptive compensation algorithm is used to correct the acceleration and integral velocity. Experiments show that the wavelet threshold denoising algorithm combined with the zero-state adaptive compensation algorithm can enhance the preciseness of the MEMS inertial sensor in object trajectory detection.
Key words: MEMS sensor / Error detection / Random errors / Drift errors
© The Authors, published by EDP Sciences, 2022
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