MEMS gyro random drift error processing method

A technology of random drift and processing method, which is applied in electrical digital data processing, special data processing applications, instruments, etc., and can solve the problems of large random drift error and low precision of MEMS gyroscope

Inactive Publication Date: 2015-11-04
苏州圣赛诺尔传感器技术有限公司
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Problems solved by technology

[0004] The purpose of the present invention is to provide a method for processing random drift errors of MEMS gyroscopes, which solves the problem of low accuracy of MEMS gyroscopes due to the large random drift errors in the output signals of MEMS gyroscopes in the prior art. The mathematical model of the MEMS gyroscope is compensated in the output to suppress the random drift error in the output signal of the MEMS gyroscope and improve the accuracy of the MEMS gyroscope

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  • MEMS gyro random drift error processing method
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  • MEMS gyro random drift error processing method

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[0030] The method for processing the random drift error of the MEMS gyroscope in this embodiment includes the following steps: (1) Using the Allan variance method to analyze the measured data of the MEMS gyroscope, separate each random error source, and determine the size of each error coefficient; (2) Perform real-time mean value processing on the data output by the gyroscope in each time interval of using the gyroscope data, and use the mean value as the use value to construct the timing random drift error model of the MEMS gyroscope; (3) According to the timing random drift error model The state space model is established, and the random error of the gyroscope is filtered multiple times by using the Kalman filter method.

[0031] The so-called Allan variance method refers to a standard method for analyzing gyroscope noise. It can easily characterize and identify various error sources and their contributions to the statistical characteristics of the entire noise. This method ...

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Abstract

The invention discloses an MEMS gyro random drift error processing method which is characterized in that based on an existing MEMS gyro and at a signal processing back-end, measured data is analyzed by an Allan variance method, various main random error sources are effectively separated and magnitude of each error coefficient is determined; time-series modeling is conducted on the basis of checking and preprocessing the data; and finally, interference noise is effectively inhibited by multiple times of Kalman filtering processing so as to raise precision of the gyro.

Description

technical field [0001] The invention belongs to the technical field of error signal processing, and in particular relates to a method for processing random drift errors of MEMS gyroscopes. Background technique [0002] Micro Electro Mechanical System (MEMS) is a new discipline developed on the basis of microelectronic technology combined with precision mechanical technology. MEMS technology has the advantages of small size, light weight, and low power consumption. Micro-inertial devices developed based on this technology are a typical type of MEMS sensors. Building a low-cost, high-performance micro-inertial navigation system has quickly become a research hotspot in the field of inertial technology. [0003] At present, the performance of MEMS gyroscopes, especially the accuracy index, still has a large gap with traditional gyroscopes, and can only be used in occasions with low precision requirements. The present invention thus comes. Contents of the invention [0004] ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C25/00G06F19/00
CPCG01C25/00
Inventor 朱捷刘松
Owner 苏州圣赛诺尔传感器技术有限公司
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