Tri Axial Gyroscope Case Study
Abstract- The paper is aimed to design and develop Graphical User Interface (GUI) named GyroDataAnalyser to enhance the statistical and stochastic analysis of the tri-axial gyroscopes. This GUI identifies the dominant stochastic noises associated with the gyroscope data using Allan Variance technique. The unique feature of this GUI is to provide the estimates of the stochastic noise coefficients without much human intervention. GUI is designed using MATLAB GUIDE environment to provide simple interface to characterise the gyroscope. This paper provides the requirement, design and implementation details for GyroDataAnalyser GUI.
Keywords: MATLAB GUI, Gyroscopes, Allan Variance, Stochastic Noise Coefficient
INTRODUCTION
Gyroscopes also known …show more content…
This process involves handling of high volume data (considering tri-axial gyroscopes) and analysing the deterministic and stochastic noises associated with gyroscope data. In this paper, we further intend to discuss the process of estimating stochastic noises of gyroscope data.
Stochastic noises involves random processes viz., Gaussian random process, Gauss-Markov random process, random walk process etc. So it is essential to identify and model the random process for the precise measurements. Allan Variance and PSD approach are the accepted …show more content…
Under statistical analysis two operations are performed viz., estimation of mean and variance. The mean and variance of the imported data is calculated using the inbuilt function mean & var respectively and the value calculated is displayed in an edit text box provided for each as shown in the Fig. 4.The provision is provided for the statistical analysis of the input data for all the three axes of the gyroscope.
2) The second component identified is the stochastic analysis of the angular rate data. The flow charts shown in the Fig. 5 are used for the computation of Allan Variance and PSD respectively. These algorithms are implemented in the call-back functions to plot the Allan Variance and PSD characteristics of all the three axes of the gyroscope. In the GyroDataAnalyser, once the input data of the respective axis is loaded, pushbuttons are used to process the Allan Variance and PSD as shown in the Fig. 4.
3) The third component identified is to find the stochastic noise coefficient of the angular rate data. GyroDataAnalyser provides the user to calculate the dominant noises as similar to typical Allan Variance
Keywords: MATLAB GUI, Gyroscopes, Allan Variance, Stochastic Noise Coefficient
INTRODUCTION
Gyroscopes also known …show more content…
This process involves handling of high volume data (considering tri-axial gyroscopes) and analysing the deterministic and stochastic noises associated with gyroscope data. In this paper, we further intend to discuss the process of estimating stochastic noises of gyroscope data.
Stochastic noises involves random processes viz., Gaussian random process, Gauss-Markov random process, random walk process etc. So it is essential to identify and model the random process for the precise measurements. Allan Variance and PSD approach are the accepted …show more content…
Under statistical analysis two operations are performed viz., estimation of mean and variance. The mean and variance of the imported data is calculated using the inbuilt function mean & var respectively and the value calculated is displayed in an edit text box provided for each as shown in the Fig. 4.The provision is provided for the statistical analysis of the input data for all the three axes of the gyroscope.
2) The second component identified is the stochastic analysis of the angular rate data. The flow charts shown in the Fig. 5 are used for the computation of Allan Variance and PSD respectively. These algorithms are implemented in the call-back functions to plot the Allan Variance and PSD characteristics of all the three axes of the gyroscope. In the GyroDataAnalyser, once the input data of the respective axis is loaded, pushbuttons are used to process the Allan Variance and PSD as shown in the Fig. 4.
3) The third component identified is to find the stochastic noise coefficient of the angular rate data. GyroDataAnalyser provides the user to calculate the dominant noises as similar to typical Allan Variance