Research on the Influence of System Calibration Method on Low-Cost MEMS Inertial Sensor Navigation Result

Low-cost microelectro mechanical systems (MEMS)-based inertial measurement unit (IMU) measurements are usually affected by inaccurate scale factors, axis misalignments, and g-sensitivity errors. These errors may significantly influence the performance of visual-inertial methods. In this paper, we propose an online IMU self-calibration method for visual-inertial systems equipped with a low-cost inertial sensor. The goal of our method is to concurrently perform 3D pose estimation and online IMU calibration based on optimization methods in unknown environments without any external equipment. To achieve this goal, we firstly develop a novel preintegration method that can handle the IMU intrinsic parameters error propagation. Then, we frame IMU calibration problem into general factors so that we can easily integrate the factors into the current graph-based visual-inertial frameworks and jointly optimize the IMU intrinsic parameters as well as the system states in a big bundle. We evaluate the proposed method with a publicly available dataset. Experimental results verify that the proposed approach is able to accurately calibrate all the considered parameters in real time, leading to significant improvement of estimation precision of visual-inertial system (VINS) compared with the estimation results with offline precalibrated IMU measurements.

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A NEW CALIBRATION METHOD FOR LOW COST MEMS INERTIAL SENSOR MODULE

Journal of Marine Science and Technology ◽

10.51400/2709-6998.1939 ◽

2010 ◽

Vol 18 (6) ◽

Author(s):

Sheng-Chih Shen ◽

Chia-Jung Chen ◽

Hsin-Jung Huang

Keyword(s):

Inertial Sensor ◽

Low Cost ◽

Calibration Method ◽

Sensor Module

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Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance

Sensors ◽

10.3390/s21072480 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2480

Author(s):

Isidoro Ruiz-García ◽

Ismael Navarro-Marchal ◽

Javier Ocaña-Wilhelmi ◽

Alberto J. Palma ◽

Pablo J. Gómez-López ◽

...

Keyword(s):

Data Fusion ◽

Reference System ◽

Inertial Sensor ◽

Low Cost ◽

Sampling Rate ◽

Sensor Data ◽

Fusion Algorithm ◽

Improve Technique ◽

Worst Case ◽

Sensor Data Fusion

In skiing it is important to know how the skier accelerates and inclines the skis during the turn to avoid injuries and improve technique. The purpose of this pilot study with three participants was to develop and evaluate a compact, wireless, and low-cost system for detecting the inclination and acceleration of skis in the field based on inertial measurement units (IMU). To that end, a commercial IMU board was placed on each ski behind the skier boot. With the use of an attitude and heading reference system algorithm included in the sensor board, the orientation and attitude data of the skis were obtained (roll, pitch, and yaw) by IMU sensor data fusion. Results demonstrate that the proposed IMU-based system can provide reliable low-drifted data up to 11 min of continuous usage in the worst case. Inertial angle data from the IMU-based system were compared with the data collected by a video-based 3D-kinematic reference system to evaluate its operation in terms of data correlation and system performance. Correlation coefficients between 0.889 (roll) and 0.991 (yaw) were obtained. Mean biases from −1.13° (roll) to 0.44° (yaw) and 95% limits of agreements from 2.87° (yaw) to 6.27° (roll) were calculated for the 1-min trials. Although low mean biases were achieved, some limitations arose in the system precision for pitch and roll estimations that could be due to the low sampling rate allowed by the sensor data fusion algorithm and the initial zeroing of the gyroscope.

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Calibration method to address influences of temperature and electrical conductivity for a low-cost soil water content sensor in the agricultural field

Agricultural Water Management ◽

10.1016/j.agwat.2021.107015 ◽

2021 ◽

Vol 255 ◽

pp. 107015

Author(s):

Yuhi Satoh ◽

Hideki Kakiuchi

Keyword(s):

Electrical Conductivity ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Low Cost ◽

Calibration Method ◽

Agricultural Field

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A Low-Cost Inertial Sensor Based on Shaped Magnetic Fluids

IEEE Transactions on Instrumentation and Measurement ◽

10.1109/tim.2011.2174902 ◽

2012 ◽

Vol 61 (5) ◽

pp. 1231-1236 ◽

Cited By ~ 9

Author(s):

Bruno Ando ◽

Salvatore Baglio ◽

Angela Beninato

Keyword(s):

Inertial Sensor ◽

Low Cost ◽

Magnetic Fluids

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A DCM Based Attitude Estimation Algorithm for Low-Cost MEMS IMUs

International Journal of Navigation and Observation ◽

10.1155/2015/503814 ◽

2015 ◽

Vol 2015 ◽

pp. 1-18 ◽

Cited By ~ 11

Author(s):

Heikki Hyyti ◽

Arto Visala

Keyword(s):

Kalman Filter ◽

Extended Kalman Filter ◽

Low Cost ◽

Direction Cosine ◽

Estimation Algorithm ◽

Calibration Method ◽

Attitude Estimation ◽

Mems Sensors ◽

Acceleration Sensors ◽

Adaptive Extended Kalman Filter

An attitude estimation algorithm is developed using an adaptive extended Kalman filter for low-cost microelectromechanical-system (MEMS) triaxial accelerometers and gyroscopes, that is, inertial measurement units (IMUs). Although these MEMS sensors are relatively cheap, they give more inaccurate measurements than conventional high-quality gyroscopes and accelerometers. To be able to use these low-cost MEMS sensors with precision in all situations, a novel attitude estimation algorithm is proposed for fusing triaxial gyroscope and accelerometer measurements. An extended Kalman filter is implemented to estimate attitude in direction cosine matrix (DCM) formation and to calibrate gyroscope biases online. We use a variable measurement covariance for acceleration measurements to ensure robustness against temporary nongravitational accelerations, which usually induce errors when estimating attitude with ordinary algorithms. The proposed algorithm enables accurate gyroscope online calibration by using only a triaxial gyroscope and accelerometer. It outperforms comparable state-of-the-art algorithms in those cases when there are either biases in the gyroscope measurements or large temporary nongravitational accelerations present. A low-cost, temperature-based calibration method is also discussed for initially calibrating gyroscope and acceleration sensors. An open source implementation of the algorithm is also available.

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Visual Measurement System for Wheel–Rail Lateral Position Evaluation

Sensors ◽

10.3390/s21041297 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1297

Author(s):

Viktor Skrickij ◽

Eldar Šabanovič ◽

Dachuan Shi ◽

Stefano Ricci ◽

Luca Rizzetto ◽

...

Keyword(s):

Measurement System ◽

Inertial Sensor ◽

Low Cost ◽

Image Point ◽

Low Velocity ◽

Point Selection ◽

Lateral Direction ◽

Initial Field ◽

Visual Measurement ◽

Track Geometry

Railway infrastructure must meet safety requirements concerning its construction and operation. Track geometry monitoring is one of the most important activities in maintaining the steady technical conditions of rail infrastructure. Commonly, it is performed using complex measurement equipment installed on track-recording coaches. Existing low-cost inertial sensor-based measurement systems provide reliable measurements of track geometry in vertical directions. However, solutions are needed for track geometry parameter measurement in the lateral direction. In this research, the authors developed a visual measurement system for track gauge evaluation. It involves the detection of measurement points and the visual measurement of the distance between them. The accuracy of the visual measurement system was evaluated in the laboratory and showed promising results. The initial field test was performed in the Vilnius railway station yard, driving at low velocity on the straight track section. The results show that the image point selection method developed for selecting the wheel and rail points to measure distance is stable enough for TG measurement. Recommendations for the further improvement of the developed system are presented.

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Gyro Drift Calibration in Low Cost Inertial System

Volume 7B: 17th Biennial Conference on Mechanical Vibration and Noise ◽

10.1115/detc99/vib-8166 ◽

1999 ◽

Author(s):

Zhong Zhao ◽

Rong Ma ◽

Weiguo Zhang

Keyword(s):

Low Cost ◽

Fuzzy Reasoning ◽

Calibration Method ◽

Inertial System ◽

Time Varying ◽

Dynamic Estimation ◽

Gyro Drift

Abstract An intelligent gyro drift calibration method for low-cost inertial system is presented in this paper. This method based on fuzzy reasoning and dynamic estimation can calibrate time-varying gyro drift in the motion of vehicle. Experiments have been done on three strapdown inertial all-attitude systems constituted of piezoelectric rate gyros. The result shows that this method is effective by which the residual of piezoelectric gyro drift can be reduced to about one percent of its original drift value.

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A Fast Calibration and Compensation Method for Magnetometers in Strap-Down Spinning Projectiles

Sensors ◽

10.3390/s18124157 ◽

2018 ◽

Vol 18 (12) ◽

pp. 4157 ◽

Cited By ~ 4

Author(s):

Dafeng Long ◽

Xiaoming Zhang ◽

Xiaohui Wei ◽

Zhongliang Luo ◽

Jianzhong Cao

Keyword(s):

Low Cost ◽

Experimental System ◽

Calibration Method ◽

Attitude Estimation ◽

Attitude Measurement ◽

Angle Error ◽

Estimation Errors ◽

Zero Bias ◽

Launch Site ◽

Spinning Projectile

Attitude measurement is an essential technology in projectile trajectory correction. Magnetometers have been used for projectile attitude measurement systems as they are small in size, lightweight, and low cost. However, magnetometers are seriously disturbed by the artillery magnetic field during launch. Moreover, the error parameters of the magnetometers, which are calibrated in advance, usually change after extended storage. The changed parameters have negative effects on attitude estimation of the projectile. To improve the accuracy of attitude estimation, the magnetometers should be calibrated again before launch or during flight. This paper presents a fast calibration method specific for a spinning projectile. At the launch site, the tri-axial magnetometer is calibrated, the parameters of magnetometer are quickly obtained by optimal ellipsoid fitting based on a least squares criterion. Then, the calibration parameters are used to compensate for magnetometer outputs during flight. The numerical simulation results show that the proposed calibration method can effectively determine zero bias, scale factors, and alignment angle errors. Finally, a semi-physical experimental system was designed to further verify the performance of the calibration method. The results show that pitch angle error reduces from 3.52° to 0.58° after calibration. The roll angle error is reduced from 2.59° to 0.65°. Simulations and experimental results indicate that the accuracy of magnetometer in strap-down spinning projectile has been greatly enhanced, and the attitude estimation errors are reduced after calibration.

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