Minimum settings calibration method for low-cost tri-axial IMU and magnetometer

Cui, Chao; Zhao, Jing; Zhu, Jianbin; Bessaad, Nassim

doi:10.1088/1361-6501/ac3ec2

Cited by 12 publications

(8 citation statements)

References 31 publications

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“…It is an adjustment between the sensor's output signal and the measured quantity to reach the closest value to the truth [75,76]. Adopting a proper calibration model can significantly affect the performance of the MEMS-based instruments [32,[76][77][78][79][80]. A MEMS pressure sensor mainly suffer from four types of error, including offset, gain, nonlinearity, and hysteresis.…”

Section: Sensor Calibrationmentioning

confidence: 99%

Development of IOT-based low-cost MEMS pressure sensor for groundwater level monitoring

Barzegar

Blanks²,

Gharehdash

et al. 2023

Meas. Sci. Technol.

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Groundwater level monitoring is critical to protect and manage of groundwater resources. A properly designed and executed instrumentation can play important role to increase the quality and reliability of collected data and reducing total monitoring costs. The efficiency of the instrumentation is mainly depending on the accuracy and reliability of the installed sensors. This study presents, the testing and application of a cost-effective pressure sensor (0-689 kPa) range) for water level monitoring based on microelectromechanical system (MEMS) technology and Internet of things (IOT) concept. The sensor performance in term of accuracy, precision, repeatability, temperature was investigated in laboratory columns (with constant water level, increasing and decreasing water levels at various rates) and in-situ conditions in an observation bore (with natural groundwater level fluctuations). The results shows that the MEMS sensor capable of providing reliable and adequate monitoring scheme with an accuracy of 0.31% full scale (FS) (2.13 kPa).

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Section: Sensor Calibrationmentioning

confidence: 99%

Development of IOT-based low-cost MEMS pressure sensor for groundwater level monitoring

Barzegar

Blanks²,

Gharehdash

et al. 2023

Meas. Sci. Technol.

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show abstract

“…If we consider it to be the result of a dynamic process rather than a static test, it can be expressed as an increase in the system noise. However, because the IMU often undergoes strict calibration before leaving the factor and with the help of mature calibration methods, system noise usually does not change significantly [28,29]. In other words, the system noise can be seen as stable.…”

Section: Ickfmentioning

confidence: 99%

An improved GNSS/INS navigation method based on cubature Kalman filter for occluded environment

Liu¹,

Shi²,

Liu³

et al. 2022

Meas. Sci. Technol.

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GNSS/INS (Global Navigation Satellite System and Inertial Navigation System) based on CKF (Cubature Kalman Filter) can provide an effective land vehicle navigation and positioning solution. The accuracy of CKF depends mainly on the prior Probability Density Function (PDF), which is inaccurate when the GNSS signal is temporarily blocked in an urban environment. Although the ICKF (Improved Cubature Kalman Filter) can reduce cubature point errors by using the historical information obtained iteratively, the generation of cubature points is still related to measurement noise. To obtain a more accurate PDF, adjustment off the sensor measurement noise is necessary. In this paper, an adaptive improved cubature Kalman filter for GNSS/INS system based on the Mahalanobis distance called MD-ICKF is proposed, which expands the usability of the micro-electronic mechanical system (MEMS) based integrated navigation system in an urban environment. Two lower triangular matrices obtained by Cholesky decomposition are used to adjust the cubature point errors during each iteration. Furthermore, the measurement noise will be inflated to obtain a more accurate PDF when it exceeds the threshold calculated by the Mahalanobis distance and Chi-square test. The field experiment results show that the proposed method has better positioning accuracy and performance than CKF and ICKF in an occluded environment

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“…There are several different errors and temperature-dependent models for triaxial MEMS sensors and corresponding calibration methods based on different principles, but they have restrictions, for instance, the need to provide accurate platforms for precise alignment or other temperature compensation devices. It is not sufficient for manufacturers to perform only basic calibration of low-cost sensors, as even small uncompensated coefficients can lead to inaccurate tilt angle estimation and increased bias in position measurements [ 13 , 14 , 15 , 16 ]. These requirements increase manufacturing costs.…”

Section: Introductionmentioning

confidence: 99%

Thermal Calibration of Triaxial Accelerometer for Tilt Measurement

Yuan

Tang

Zhang

et al. 2023

Sensors

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The application of MEMS accelerometers used to measure inclination is constrained by their temperature dependence, and each accelerometer needs to be calibrated individually to increase stability and accuracy. This paper presents a calibration and thermal compensation method for triaxial accelerometers that aims to minimize cost and processing time while maintaining high accuracy. First, the number of positions to perform the calibration procedure is optimized based on the Levenberg-Marquardt algorithm, and then, based on this optimized calibration number, thermal compensation is performed based on the least squares method, which is necessary for environments with large temperature variations, since calibration parameters change at different temperatures. The calibration procedures and algorithms were experimentally validated on marketed accelerometers. Based on the optimized calibration method, the calibrated results achieved nearly 100 times improvement. Thermal drift calibration experiments on the triaxial accelerometer show that the thermal compensation scheme in this paper can effectively reduce drift in the temperature range of −40 °C to 60 °C. The temperature drifts of x- and y-axes are reduced from −13.2 and 11.8 mg to −0.9 and −1.1 mg, respectively. The z-axis temperature drift is reduced from −17.9 to 1.8 mg. We have conducted various experiments on the proposed calibration method and demonstrated its capacity to calibrate the sensor frame error model (SFEM) parameters. This research proposes a new low-cost and efficient strategy for increasing the practical applicability of triaxial accelerometers.

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Minimum settings calibration method for low-cost tri-axial IMU and magnetometer

Cited by 12 publications

References 31 publications

Development of IOT-based low-cost MEMS pressure sensor for groundwater level monitoring

Development of IOT-based low-cost MEMS pressure sensor for groundwater level monitoring

An improved GNSS/INS navigation method based on cubature Kalman filter for occluded environment

Thermal Calibration of Triaxial Accelerometer for Tilt Measurement

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