Improvement of Electronic Compass Accuracy Based on Magnetometer and Accelerometer Calibration

Šipoš, Martin; Rohác, J; Nováček, Petr

doi:10.12693/aphyspola.121.945

Cited by 11 publications

(4 citation statements)

References 9 publications

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“…It is important to note that gravity varies based on the object's latitude and height. The modified pitch angle can be estimated as in Equation (3).…”

Section: Pitch and Roll Angle Calculationmentioning

confidence: 99%

“…In urban environments, GNSS signals can be obstructed by tall buildings, affected by multipath interference, or even subjected to deliberate jamming, all of which can significantly impact navigation accuracy. To improve accuracy, AVs often employ a combination of sensors [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Machine Learning-Based ANFIS Calibrated RISS/GNSS Integration for Improved Navigation in Urban Environments

Mahdi,

Azouz,

Noureldin

et al. 2024

Sensors

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Autonomous vehicles (AVs) require accurate navigation, but the reliability of Global Navigation Satellite Systems (GNSS) can be degraded by signal blockage and multipath interference in urban areas. Therefore, a navigation system that integrates a calibrated Reduced Inertial Sensors System (RISS) with GNSS is proposed. The system employs a machine-learning-based Adaptive Neuro-Fuzzy Inference System (ANFIS) as a novel calibration technique to improve the accuracy and reliability of the RISS. The ANFIS-based RISS/GNSS integration provides a more precise navigation solution in such environments. The effectiveness of the proposed integration scheme was validated by conducting tests using real road trajectory and simulated GNSS outages ranging from 50 to 150 s. The results demonstrate a significant improvement in 2D position Root Mean Square Error (RMSE) of 43.8% and 28% compared to the traditional RISS/GNSS and the frequency modulated continuous wave (FMCW) Radar (Rad)/RISS/GNSS integrated navigation systems, respectively. Moreover, an improvement of 47.5% and 23.4% in 2D position maximum errors is achieved compared to the RISS/GNSS and the Rad/RISS/GNSS integrated navigation systems, respectively. These results reveal significant improvements in positioning accuracy, which is essential for safe and efficient navigation. The long-term stability of the proposed system makes it suitable for various navigation applications, particularly those requiring continuous and precise positioning information. The ANFIS-based approach used in the proposed system is extendable to other low-end IMUs, making it an attractive option for a wide range of applications.

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“…It is important to note that gravity varies based on the object's latitude and height. The modified pitch angle can be estimated as in Equation (3).…”

Section: Pitch and Roll Angle Calculationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Machine Learning-Based ANFIS Calibrated RISS/GNSS Integration for Improved Navigation in Urban Environments

Mahdi,

Azouz,

Noureldin

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…Sipos et al used a thin-shell method to determine sensor error models so that the accuracy of a pitch and a roll angle evaluation was improved. Experimental results showed that the root mean square error (RMSE) of the roll and pitch measured after correction were 0.462 • and 0.567 • , which were 1.270 • and 2.012 • , respectively, without correction, while the true value of both was 20 • [25]. However, the mathematical relationship between error sources and pitch measurement errors was still unclear.…”

Section: Introductionmentioning

confidence: 99%

A method for improving the performance of centering rod surveying based on two-position correction

Dai¹,

Pan²,

Yang³

et al. 2022

Meas. Sci. Technol.

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Aiming at the problem that accelerometer’s bias and scale factor error decrease the measurement accuracy of centering rod surveying, a performance improving method for pitch measurement is proposed. The error model of centering rod surveying is built so that the relationship between pitch measurement error and accelerometer’s bias and scale factor error are clear. Numerical simulations are conduced out and the error variation is revealed. A two-position correction method is come up and twelve verification experiments are carried out. After correction, the measurement error is reduced from a few centimeters to submillimeter scale. Experimental results illustrate that the accuracy of pitch measurement is improved effectively, which meets the requirements for use. Three repeated experiments are carried out, the calculated uncertainties are 0.053 %, 0.035 % and 0.027 % separately, which indicates the feasibility and effectiveness of the proposed method in practical applications. It can provide some guidance for improving the performance of centering rod surveying.

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“…The calibration is generally crucial for the MEMS units applications. Calibration techniques can be further divided into two groups depending on whether or not they use precise positioning and measuring devices to obtain referential data [1], [6] or they utilize information just about applied forces without knowledge of an exact positioning [7], [8], [9], [10], [11], [12]. The linear model for accurate tilt sensing and estimated sensor error model was proposed in [13].…”

Section: Introductionmentioning

confidence: 99%

Modified Biaxial Accelerometer Framework in G-sensing Mode

Rohác

Šipoš

Ďaďo

2020

TEE

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This paper deals with an acceleration measuring unit, which uses two biaxial accelerometers, and compares its performance with a typical triaxial framework. In cases of small aircrafts, UAVs, robots, or terrestrial vehicle navigation units utilizing sensors manufactured by a MEMS technology are preferred due to their cost-effectiveness. In order to suppress imperfections of the measuring system (noise, drift, nonlinearities, small sensitivity) a solution based on the difference configuration of accelerometers is proposed.

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Improvement of Electronic Compass Accuracy Based on Magnetometer and Accelerometer Calibration

Cited by 11 publications

References 9 publications

A Novel Machine Learning-Based ANFIS Calibrated RISS/GNSS Integration for Improved Navigation in Urban Environments

A Novel Machine Learning-Based ANFIS Calibrated RISS/GNSS Integration for Improved Navigation in Urban Environments

A method for improving the performance of centering rod surveying based on two-position correction

Modified Biaxial Accelerometer Framework in G-sensing Mode

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