An MEMS gyro denoising method based on a wavelet threshold

A wavelet threshold and gyro technology, applied in the field of random error compensation, can solve the problems of unsuitable calculation processing, poor fault tolerance, inaccurate statistics, etc., and achieve the effect of reducing random errors of MEMS gyro, simple calculation and easy realization

Active Publication Date: 2019-02-15
LANZHOU JIAOTONG UNIV
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Problems solved by technology

The general modeling compensation method relies too much on the established model and prior statistical information, and the fault tolerance is not only bad but also inaccurate statistics will cause this method to fail
Although th

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  • An MEMS gyro denoising method based on a wavelet threshold
  • An MEMS gyro denoising method based on a wavelet threshold
  • An MEMS gyro denoising method based on a wavelet threshold

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[0038] 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.

[0039] The wavelet transform algorithm is especially suitable for describing the characteristics of non-stationary signals because of its excellent multi-resolution characteristics, which is convenient for the feature extraction and protection of the original signal, and the wavelet transform calculation is simple and the filtering effect is good.

[0040] Such as figure 1 Shown, a kind of MEMS gyroscope denoising method based on wavelet threshold, comprising:

[0041] S101: sampling the MEMS gyroscope signal;

[0042] S102: Perform trend analysis on the MEMS gyroscope signal,

[0043] That is to analyze the trend of the output characteristics of the MEMS gyroscop...

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Abstract

The invention discloses an MEMS gyro denoising method based on a wavelet threshold, which comprises the following steps of sampling a MEMS gyro signal; performing the trend analysis on the MEMS gyro signal; determining the wavelet bases and decomposition layers based on the results of trend analysis, selecting the wavelet coefficient transform function based on the determined wavelet basis and decomposition layer number, and distinguishing the noise and detail of the signal based on the selected wavelet coefficient transform function, selecting threshold functions and thresholds to remove thenoise components from the detailed part of the signal. By analyzing the output signal of MEMS gyroscope, the drift of MEMS gyroscope has a linear trend, which is a slow-changing process. The analysisshows that the output signal of MEMS gyroscope is a stationary signal with low frequency. On the basis of analysis, the influence of random error of MEMS gyroscope is reduced, and the real-time outputprecision of MEMS gyroscope sensor is improved. Because only wavelet coefficient transform is used, the calculation is simple, is easy to realize and has the advantage of high precision.

Description

technical field [0001] The invention relates to the field of random error compensation of MEMS micromechanical gyroscopes in integrated navigation, in particular to a method for denoising MEMS gyroscopes based on wavelet thresholds. Background technique [0002] At present, the output signal of the MEMS gyroscope is a typical non-stationary sequence, and in actual use, the error will continue to accumulate due to the complex and changeable environment, and the random error of the gyroscope is the main reason affecting the accuracy of the MEMS gyroscope. [0003] Common MEMS gyroscope noise reduction methods include modeling compensation, artificial intelligence algorithm and wavelet transform algorithm, etc. The general modeling compensation method relies too much on the established model and prior statistical information, and the fault tolerance is not only bad but also inaccurate statistics will cause this method to fail. Although the artificial intelligence neural networ...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06F2218/06
Inventor 杨菊花陈光武张琳婧王迪李文元程鉴皓刘射德刘昊
Owner LANZHOU JIAOTONG UNIV
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