MEMS (micro-electromechanical system) gyroscope random error modeling filtering method based on modified EMD (empirical mode decomposition)

A random error and gyro technology, which is applied in the field of MEMS gyro random error modeling and filtering based on improved EMD, can solve the problems of insufficient theoretical support, prone to over-fitting, complex network structure operation, etc., so as to improve the fitting accuracy and reduce the The effect of small computational complexity

Inactive Publication Date: 2019-05-24
LANZHOU JIAOTONG UNIV +1
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Problems solved by technology

[0003] In recent years, scholars at home and abroad have conducted a lot of in-depth research on the random drift of MEMS gyroscopes, but these methods have their own advantages and disadvantages. Although the wavelet analysis method has a high resolution in the time-frequency domain, the process is complicated and the wavelet basis function The selection and fixed decomposition scale lead to its lack of good adaptability; the neural network modeling method theoretically has the ability to approximate nonlinear functions with arbitrary precision and has high-speed parallel computing capabilities, but it has a complex network structure and it is prone to over-fitting problems; and the method of time series analysis and the establishm...

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  • MEMS (micro-electromechanical system) gyroscope random error modeling filtering method based on modified EMD (empirical mode decomposition)
  • MEMS (micro-electromechanical system) gyroscope random error modeling filtering method based on modified EMD (empirical mode decomposition)
  • MEMS (micro-electromechanical system) gyroscope random error modeling filtering method based on modified EMD (empirical mode decomposition)

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[0050] The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

[0051] like figure 1 As shown, a MEMS gyroscope random error modeling and filtering method based on improved EMD, including:

[0052] Use the EMD algorithm to extract the IMF component in the original signal;

[0053] modeling based on the extracted IMF components;

[0054] Kalman filtering is performed on the model obtained by modeling, and the random error of the MEMS gyroscope is compensated in real time.

[0055] Optionally, the extraction of the IMF component from the original signal using the EMD algorithm includes:

[0056] Use the EMD algorithm to decompose the original signal into the sum of multiple IMFs and non-random terms;

[0057] Calculate the aut...

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Abstract

The invention discloses an MEMS (micro-electromechanical system) gyroscope random error modeling filtering method based on modified EMD (empirical mode decomposition), which comprises extracting an IMF (intrinsic mode function) component from an original signal through the EMD algorithm; modeling based on the extracted IMF component; subjecting a model formed by modeling to Kalman filtering, and compensating MEMS gyroscope random errors in real time. Measurement precision of a MEMS gyroscope can be improved.

Description

technical field [0001] The invention relates to the field of micro-electromechanical systems, in particular to an improved EMD-based MEMS gyroscope random error modeling and filtering method. Background technique [0002] With the rapid development of modern microelectronics and micromachining technology, MEMS gyroscopes based on MicroElectromechanical System (MEMS) technology are developing rapidly. Compared with other types of gyroscopes, MEMS gyroscopes are miniaturized and inexpensive. Low power consumption, easy installation and other advantages. MEMS has great development space and development value. At present, it has been more and more widely used in many fields. However, due to the characteristics of the components and the influence of the external environment, the measurement accuracy of the MEMS gyroscope is relatively low, and the random drift error is the main error source affecting the accuracy of the gyroscope. Therefore, in order to improve the stability a...

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Application Information

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IPC IPC(8): G01C25/00G06K9/62G06F17/18
Inventor 陈光武刘洋杨菊花程鉴皓
Owner LANZHOU JIAOTONG UNIV
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