Analysis of the errors of MEMS accelerometers by the Allan variation method

Rudyk, Andrii

doi:10.26642/tn-2017-1(79)-100-109

Cited by 3 publications

(12 citation statements)

References 2 publications

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“…Frequency analysis methods considering power spectral density (PSD) [ 11 ] and temporal analysis techniques considering the Allan variance (AVAR) [ 12 , 13 , 14 , 15 ] are applied to examine the gyroscope random errors.…”

Section: Methods Of Analyzing Random Errors In Gyroscopesmentioning

confidence: 99%

“…Typically, the basic systematic error of a gyroscope will be different from the basic systematic error of another gyroscope of the same type. That is because a group of similar gyroscopes the main systematic error is considered as a random error, but constant in the operating cycle [ 11 , 17 , 18 ].…”

Section: Methods Of Analyzing Random Errors In Gyroscopesmentioning

confidence: 99%

“…A generalized equation of gyroscope errors obtained in [ 11 , 19 ] is

where

is the diagonal matrix of relative errors of gyroscope conversion coefficients [%];

is the skew-symmetric matrix corresponding to the matrix of directional cosines

;

is the gyroscope zero offset vector with dimension of this gyroscope output signal.…”

Section: Analysis Of the Gyroscope Random Error Componentsmentioning

confidence: 99%

“…The random error components of gyroscopes, which are inertial sensors, are defined by the presence of noise and noisy processes of various kinds [ 11 , 20 ]:

where

is the random error component caused by white noise ( WN );

is the bias instability ( BI );

is the random rate walk ( RRW );

is the of the random error component caused by the exponential correlated (Markov) noise ( MN ).…”

Section: Analysis Of the Gyroscope Random Error Componentsmentioning

confidence: 99%

“…While analyzing the SINS accuracy characteristics caused by the gyroscope errors, attention is paid to zero instability (offset) and residual systematic errors. This paper focuses on the instability of gyroscope’s zeros, which typically represent a sum of systematic

(Systematic Error) and random

(Random Error) components [ 11 ]:

…”

Section: Introductionmentioning

confidence: 99%

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Strapdown Inertial Navigation Systems for Positioning Mobile Robots—MEMS Gyroscopes Random Errors Analysis Using Allan Variance Method

Rudyk

Семенов

Kryvinska

et al. 2020

Sensors

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A problem of estimating the movement and orientation of a mobile robot is examined in this paper. The strapdown inertial navigation systems are often engaged to solve this common obstacle. The most important and critically sensitive component of such positioning approximation system is a gyroscope. Thus, we analyze here the random error components of the gyroscope, such as bias instability and random rate walk, as well as those that cause the presence of white and exponentially correlated (Markov) noise and perform an optimization of these parameters. The MEMS gyroscopes of InvenSense MPU-6050 type for each axis of the gyroscope with a sampling frequency of 70 Hz are investigated, as a result, Allan variance graphs and the values of bias instability coefficient and angle random walk for each axis are determined. It was found that in the output signals of the gyroscopes there is no Markov noise and random rate walk, and the X and Z axes are noisier than the Y axis. In the process of inertial measurement unit (IMU) calibration, the correction coefficients are calculated, which allow partial compensating the influence of destabilizing factors and determining the perpendicularity inaccuracy for sensitivity axes, and the conversion coefficients for each axis, which transform the sensor source codes into the measure unit and bias for each axis. The output signals of the calibrated gyroscope are noisy and offset from zero to all axes, so processing accelerometer and gyroscope data by the alpha-beta filter or Kalman filter is required to reduce noise influence.

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Section: Methods Of Analyzing Random Errors In Gyroscopesmentioning

confidence: 99%

Section: Methods Of Analyzing Random Errors In Gyroscopesmentioning

confidence: 99%

“…A generalized equation of gyroscope errors obtained in [ 11 , 19 ] is

where

is the diagonal matrix of relative errors of gyroscope conversion coefficients [%];

is the skew-symmetric matrix corresponding to the matrix of directional cosines

;

is the gyroscope zero offset vector with dimension of this gyroscope output signal.…”

Section: Analysis Of the Gyroscope Random Error Componentsmentioning

confidence: 99%

“…The random error components of gyroscopes, which are inertial sensors, are defined by the presence of noise and noisy processes of various kinds [ 11 , 20 ]:

where

is the random error component caused by white noise ( WN );

is the bias instability ( BI );

is the random rate walk ( RRW );

is the of the random error component caused by the exponential correlated (Markov) noise ( MN ).…”

Section: Analysis Of the Gyroscope Random Error Componentsmentioning

confidence: 99%

(Systematic Error) and random

(Random Error) components [ 11 ]:

…”

Section: Introductionmentioning

confidence: 99%

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Strapdown Inertial Navigation Systems for Positioning Mobile Robots—MEMS Gyroscopes Random Errors Analysis Using Allan Variance Method

Rudyk

Семенов

Kryvinska

et al. 2020

Sensors

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Devising a method for measuring the motion parameters of industrial equipment in the quarry using adaptive parameters of a video sequence

Подчашинський

Лугових

Tsyporenko

et al. 2021

EEJET

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The method and structural scheme of an information-measuring system for determining the parameters of objects' movements (technological equipment in the quarry for extracting block natural stone) have been proposed. A distinctive feature of time video sequences containing images of measured objects is their adaptation and adjustment in accordance with the intensity of movement and accuracy requirements for measurement results. Structural and software-algorithmic methods were also applied for improving the accuracy of measurements of motion parameters, namely: complexation of two measuring channels and exponential smoothing of digital references. One of the measuring channels is based on a digital video camera, the second is based on an accelerometer mounted on an object and two integrators. Exponential smoothing makes it possible to take into consideration the previous countdowns of movement parameters with weight coefficients. That ensures accounting for the existing patterns of movement of the object and reducing the errors when measuring the parameters of movement by (1.4...1.6) times. The resulting solutions have been implemented in the form of an information and measurement system. The technological process of extracting blocks of natural stone in the quarry was experimentally investigated using a diamond-rope installation. Based on the contactless measurement of motion parameters, it is possible to ensure control over this process and improve the quality of blocks made of natural stone. Based on the experimental study of measurement errors, recommendations were given for the selection of adaptive parameters of a video sequence, namely the size of images and the value of the inter-frame interval. In addition, methods for the software-algorithmic processing of measuring information were selected, specifically exponential smoothing and averaging the coordinates of the contour of an object, measured in 30 adjacent lines of the image

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Research and Simulation of the Local Navigation System of Terrestrial Mobile Robot

Rudyk

Matei

2020

IAPGOS

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The algorithm of complex information processing in the local navigation system of a terrestrial mobile robot and its physical model is developed. Experimental researches of this physical model have been carried out, as a result of which qualitative characteristics of the developed local navigation system have been determined. The trajectory of the object, based on the calculated navigation parameters, has a configuration identical to the actually passed route (adequate functioning of the system as a course indicator). The error in determining the coordinates of an offline object has value 0.012t2 (1.2 m per 10 s) when moving linearly and 0.022t2 (2.2 m per 10 s) when maneuvering. The orientation angles are worked out with precision (0.1÷0.3)о for roll and pitch angles and (2÷3)о for the angle of the course. Precise characteristics of the developed physical model LNS for determining orientation angles and motion parameters МR similar to the passport serial data SINS, and in some cases due to navigation features МR show even better accuracy.

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Analysis of the errors of MEMS accelerometers by the Allan variation method

Abstract: ANALYSIS OF THE ERRORS OF MEMS ACCELEROMETERS BY THE ALLAN VARIATION METHOD

Cited by 3 publications

References 2 publications

Strapdown Inertial Navigation Systems for Positioning Mobile Robots—MEMS Gyroscopes Random Errors Analysis Using Allan Variance Method

Strapdown Inertial Navigation Systems for Positioning Mobile Robots—MEMS Gyroscopes Random Errors Analysis Using Allan Variance Method

Devising a method for measuring the motion parameters of industrial equipment in the quarry using adaptive parameters of a video sequence

Research and Simulation of the Local Navigation System of Terrestrial Mobile Robot

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