The Use of Allan Variation in the Study of the Random Errors of Angular Rate Sensors

2021 ◽  
Vol 23 (3) ◽  
pp. 153-157
Author(s):  
A.V. Miheev ◽  
◽  
S.A. Anchutin ◽  
E.S. Kochurina ◽  
A.S. Timoshenkov ◽  
...  
Keyword(s):  
Random Walk ◽  
Angular Rate ◽  
Random Errors ◽  
Allan Variation ◽  
Bias Instability

This paper describes the use of Allan variation in the study of the random errors of angular rate sensors. The results of the study are presented: Allan diagram, Angle Random Walk, Bias Instability.

Modeling Study on Random Error of Fiber Optic Gyro

2012 ◽  
Vol 239-240 ◽  
pp. 167-171
Author(s):  
Fan Zhang
Keyword(s):  
Random Walk ◽  
Random Error ◽  
Fiber Optic ◽  
Angular Rate ◽  
Measurement Unit ◽  
Random Errors ◽  
Fiber Optic Gyro ◽  
Zero Bias ◽  
Instability Rate ◽  
Bias Instability

An accurate modeling method for the random error of the fiber optic gyro (FOG) is presented. Taking the FOG in the inertial measurement unit of one specific inertial navigation system as the subject investigated, the method is composed of the data acquisition, preprocessing, establishing the FOG AR(2) model and performing Kalman filtering based on the model. The filtering result and the Allan variance analysis of FOG prove that the method effectively reduces the FOG random error, decreasing the angle random walk, zero-bias instability, rate random walk, angular rate ramp and quantification noise of FOG signals to less than one half of the corresponding values before the filtering of FOG random errors, which improves the accuracy of FOG.

The Gyro Random Walk Analysis Based on Allan Variance

2014 ◽  
Vol 668-669 ◽  
pp. 953-956
Author(s):  
Xiao Yan Dai ◽  
Zhi Gang Chen ◽  
Xian Xie
Keyword(s):  
Random Walk ◽  
Allan Variance ◽  
Experimental Result ◽  
Estimation Accuracy ◽  
Motion Processing ◽  
Output Data ◽  
Random Migration ◽  
Bias Instability ◽  
Static Output ◽  
Random Walk Analysis

In this paper, we did the analysis of the gyro random migration using Allan variance method, static output data using a three-axis gyroscope of the global first integrated six-axis motion processing components MPU6050. Experimental result shows that the fitting of bias instability and angle random walk smoother, it not only improves the estimation accuracy of random walk coefficient, but also the amount of data required is greatly reduced.

scholarly journals Estimation of inertial sensors error impact on platformless inertial navigation system accuracy

2018 ◽  
pp. 29-34 ◽  
Author(s):  
S. V. Andreyev ◽  
V. V. Ilinykh ◽  
O. A. Ilinykh ◽  
M. S. Chertkov ◽  
A. V. Klyuchnikov
Keyword(s):  
Random Walk ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Sensors ◽  
Inertial Navigation ◽  
Error Model ◽  
Bias Instability ◽  
Laser Gyroscopes ◽  
Sensor Assembly ◽  
Mathematical Error

The study describes a mathematical error model of a platformless inertial navigation system and focuses on using Allan variance as a method for estimating such instrumental errors of sensors, such as zero signal bias instability, angle random walk and rate random walk. The paper shows the results of the work of the mathematical error model, the model being constructed using the estimated instrumental errors of a sample of sensor assembly which consists of three ring laser gyroscopes and a three-axis accelerometer unit.

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

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4841 ◽  
Author(s):  
Andrii V. Rudyk ◽  
Andriy O. Semenov ◽  
Natalia Kryvinska ◽  
Olena O. Semenova ◽  
Volodymyr P. Kvasnikov ◽  
...  
Keyword(s):  
Inertial Navigation ◽  
Allan Variance ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Random Errors ◽  
Inertial Navigation Systems ◽  
Mems Gyroscopes ◽  
Bias Instability ◽  
Errors Analysis ◽  
Strapdown Inertial Navigation

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.

scholarly journals Performance Enhancement of Consumer-Grade MEMS Sensors through Geometrical Redundancy

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4851
Author(s):  
Giorgio de Alteriis ◽  
Domenico Accardo ◽  
Claudia Conte ◽  
Rosario Schiano Lo Moriello
Keyword(s):  
Random Walk ◽  
Performance Enhancement ◽  
Inertial Sensors ◽  
Low Cost ◽  
Cost Effective ◽  
Measurement Procedure ◽  
Measurement Unit ◽  
Mems Sensors ◽  
Mems Technology ◽  
Bias Instability

The paper deals with performance enhancement of low-cost, consumer-grade inertial sensors realized by means of Micro Electro-Mechanical Systems (MEMS) technology. Focusing their attention on the reduction of bias instability and random walk-driven drift of cost-effective MEMS accelerometers and gyroscopes, the authors hereinafter propose a suitable method, based on a redundant configuration and complemented with a proper measurement procedure, to improve the performance of low-cost, consumer-grade MEMS sensors. The performance of the method is assessed by means of an adequate prototype and compared with that assured by a commercial, expensive, tactical-grade MEMS inertial measurement unit, taken as reference. Obtained results highlight the promising reliability and efficacy of the method in estimating position, velocity, and attitude of vehicles; in particular, bias instability and random walk reduction greater than 25% is, in fact, experienced. Moreover, differences as low as 0.025 rad and 0.89 m are obtained when comparing position and attitude estimates provided by the prototype and those granted by the tactical-grade MEMS IMU.

scholarly journals Performance of Quad Mass Gyroscope in the Angular Rate Mode

Micromachines ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 266
Author(s):  
Sina Askari ◽  
Mohammad Asadian ◽  
Andrei Shkel
Keyword(s):  
Angular Rate ◽  
Open Loop ◽  
Q Factor ◽  
Control Loops ◽  
Noise Characteristics ◽  
Trade Offs ◽  
Power Spectral ◽  
Mode Of Operation ◽  
Q Factors ◽  
Bias Instability

In this paper, the characterization and analysis of a silicon micromachined Quad Mass Gyroscope (QMG) in the rate mode of operation are presented. We report on trade-offs between full-scale, linearity, and noise characteristics of QMGs with different Q-factors. Allan Deviation (ADEV) and Power Spectral Density (PSD) analysis methods were used to evaluate the performance results. The devices in this study were instrumented for the rate mode of operation, with the Open-Loop (OL) and Force-to-Rebalance (FRB) configurations of the sense mode. For each method of instrumentation, we presented constraints on selection of control parameters with respect to the Q-factor of the devices. For the high Q-factor device of over 2 million, and uncompensated frequency asymmetry of 60 mHz, we demonstrated bias instability of 0.095∘/hr and Angle Random Walk (ARW) of 0.0107∘/hr in the OL mode of operation and bias instability of 0.065∘/hr and ARW of 0.0058∘/hr in the FRB mode of operation. We concluded that in a realistic MEMS gyroscope with imperfections (nearly matched, but non-zero frequency asymmetry), a higher Q-factor would increase the frequency stability of the drive axis resulting in an improved noise performance, but has challenges in implementation of digital control loops.

scholarly journals An Adaptive Filtering Approach Based on the Dynamic Variance Model for Reducing MEMS Gyroscope Random Error

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3943 ◽  
Author(s):  
Yanshun Zhang ◽  
Chuang Peng ◽  
Dong Mou ◽  
Ming Li ◽  
Wei Quan
Keyword(s):  
Adaptive Filtering ◽  
Random Error ◽  
Error Compensation ◽  
Angular Rate ◽  
Micro Electro Mechanical System ◽  
Random Errors ◽  
Variance Model ◽  
Rate Condition ◽  
Mems Gyroscope ◽  
Filtering Approach

To improve the dynamic random error compensation accuracy of the Micro Electro Mechanical System (MEMS) gyroscope at different angular rates, an adaptive filtering approach based on the dynamic variance model was proposed. In this paper, experimental data were utilized to fit the dynamic variance model which describes the nonlinear mapping relations between the MEMS gyroscope output data variance and the input angular rate. After that, the dynamic variance model was applied to online adjustment of the Kalman Filter measurement noise coefficients. The proposed approach suppressed the interference from the angular rate in the filtering results. Dynamic random errors were better estimated and reduced. Turntable experiment results indicated that the adaptive filtering approach compensated for the MEMS gyroscope dynamic random error effectively both in the constant angular rate condition and the continuous changing angular rate condition, thus achieving adaptive dynamic random error compensation.

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