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MEMS gyroscope signal denoising method based on self-adaptive multi-scale filter

An adaptive and filter technology, applied in the direction of instruments, measuring devices, etc., can solve difficult problems such as signal distortion, achieve the effect of making up for defects, avoiding signal distortion, and ensuring denoising effect

Inactive Publication Date: 2021-06-25
TIANJIN UNIV
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Problems solved by technology

However, the traditional SG filter uses a fixed window length for smoothing, and it is difficult to avoid signal distortion while obtaining a good denoising effect.

Method used

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  • MEMS gyroscope signal denoising method based on self-adaptive multi-scale filter
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  • MEMS gyroscope signal denoising method based on self-adaptive multi-scale filter

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Embodiment Construction

[0036] The present invention will be further described below in conjunction with the accompanying drawings.

[0037] The present invention is based on the MEMS gyroscope signal denoising method of the self-adaptive multi-scale filter, and the specific implementation process is as follows:

[0038] Step 1: Collect the MEMS gyroscope signal, and calculate the sample variance of the signal at each sampling point.

[0039] First, choose W max , W min , lambda th , K as the initial input value; where, W max is the maximum value of the left window length and the right window length of the SG filter, W min is the minimum value of the left window length and right window length of the SG filter, λ th Is the sample variance threshold used to detect mutation signals. According to this value, the left and right window lengths of the SG filter can be adaptively adjusted, and K is the order of the SG filter. The selection of these values ​​depends on experience. For the same type of g...

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Abstract

The invention discloses an MEMS gyroscope signal denoising method based on a self-adaptive multi-scale filter. The method comprises the following steps: acquiring MEMS gyroscope signals, and calculating sample variances of the signals at sampling points; adaptively adjusting the left window length and the right window length of each data point in the SG filter according to the sample variance of each data point in the signal and preset maximum and minimum window lengths; and performing adaptive multi-scale SG filtering on each sampling point signal by using the obtained left and right window lengths of each sampling point. In order to realize rapid compensation for random errors of MEMS gyroscope signals, a mapping model is established for sample variance based on adaptive moving average and the window length of an SG filter, and the window length of the SG filter is adaptively adjusted, so that de-noising of non-stationary and non-linear gyroscope signals is realized, and the multi-scale window length enables the filter not to cause signal deformation while achieving a good denoising effect.

Description

technical field [0001] The invention mainly relates to the technical field of low-cost MEMS gyroscope output signal processing, belongs to inertial navigation, and more specifically relates to a MEMS gyroscope signal denoising method based on an adaptive multi-scale filter. Background technique [0002] Compared with traditional inertial measurement components, MEMS gyroscopes have the advantages of small size, light weight, low cost, low power consumption, impact resistance, and high reliability, and have important application value for measuring the angular velocity of moving objects. However, due to the imperfection of MEMS theory and technology, there is a large noise in the output signal, and its accuracy is 1 to 3 orders of magnitude lower than that of traditional inertial devices. The accuracy of the MEMS gyroscope will decrease rapidly with time, so the error of the MEMS gyroscope needs to be compensated. [0003] The error of MEMS gyroscope consists of two parts: d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C25/00
CPCG01C25/005
Inventor 孙长库何晶晶王鹏
Owner TIANJIN UNIV
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