Calibration methods for inertial and magnetic sensors

Bonnet, Stéphane; Bassompierre, Cindy; Godin, Christelle; Lesecq, Suzanne; Barraud, Alain

doi:10.1016/j.sna.2009.10.008

Cited by 157 publications

(98 citation statements)

References 13 publications

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“…The rationale is that of using a dead reckoning-like approach [8,9]: detect the human steps by means of a proper analysis of the accelerometer measurements [33], then use the combination of magnetometer and accelerometer measurements to estimate the movement direction with respect to the north [28].…”

Section: System Description and Relation To Previous Workmentioning

confidence: 99%

A Particle Filter for Smartphone-Based Indoor Pedestrian Navigation

et al. 2014

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This paper considers the problem of indoor navigation by means of low-cost mobile devices. The required accuracy, the low reliability of low-cost sensor measurements and the typical unavailability of the GPS signal make indoor navigation a challenging problem. In this paper, a particle filtering approach is presented in order to obtain good navigation performance in an indoor environment: the proposed method is based on the integration of information provided by the inertial navigation system measurements, the radio signal strength of a standard wireless network and of the geometrical information of the building. In order to make the system as simple as possible from the user's point of view, sensors are assumed to be uncalibrated at the beginning of the navigation, and an auto-calibration procedure of the magnetic sensor is performed to improve the system performance: the proposed calibration procedure is performed during regular user's motion (no specific work is required). The navigation accuracy achievable with the proposed method and the results of the auto-calibration procedure are evaluated by means of a set of tests carried out in a university building.

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Section: System Description and Relation To Previous Workmentioning

confidence: 99%

A Particle Filter for Smartphone-Based Indoor Pedestrian Navigation

et al. 2014

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“…In this paper, we propose a two-step parameter estimation scheme to ease the optimization process, i.e., 1) the sensor bias b k is estimated separately; 2) Unlike Bonnet. et al [21] estimating the other 9 parameters …”

Section: B Inertial Sensor Calibrationmentioning

confidence: 99%

Calibration of Miniature Inertial and Magnetic Sensor Units for Robust Attitude Estimation

Zhang

Yang

2014

IEEE Trans. Instrum. Meas.

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Abstract-Attitude estimation from miniature inertial and magnetic sensors has been used in a wide variety of applications, ranging from virtual reality, underwater vehicles, handheld navigation devices, to biomotion analysis. However, appropriate sensor calibrations for accurate sensor measurements are essential to the performance of attitude estimation algorithms. In this paper, we present a robust sensor calibration method for accurate attitude estimation from 3-axis accelerometers, gyroscopes and magnetometer measurements. The proposed calibration method only requires a simple pan-tilt unit. A unified sensor model for inertial and magnetic sensors is used to convert the sensor readings to physical quantities in metric units. Based on the sensor model, a cost function is constructed, and a two-step iterative algorithm is then proposed to calibrate the inertial sensors. Due to the difficulties of acquiring the ground-truth of the Earth magnetic field, a simplified pseudo-magnetometer calibration method is also presented based on an ellipsoid fitting algorithm. The calibration method is then applied to our sensor nodes, and the good performance of the orientation estimation has illustrated the effectiveness of the proposed sensor calibration method.

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“…Mathematically, these errors are modeled as total non-orthogonality, total scale factor and total bias, which are the main results calibrated by most calibration methods [5,8]. A unified mathematical model is used as follows: under the assumption that the z-axis of s-frame coincides with the z-axis of b-frame [5]. n is measurement noise vector, which is generally assumed to be white and Gaussian and is denoted as ( )…”

Section: B Magnetometer Errro Modelmentioning

confidence: 99%

“…Gebre-Egziabher [4] pointed out that a data collection scheme must be performed to reduce the effect of measurement locus, but did not describe the scheme in detail. Bonnet [5] took three data sets obtained from different movements (free rotations, rotations around East-West axis, and six static orientations) for simulated calibration comparison. Based on the simulation results, he concluded that some calibration methods are lack of robustness when measurement points are not well distributed.…”

Section: Introduction (Heading 1)mentioning

confidence: 99%

D-Optimal Design Applied to Calibration of Strapdown Three-axis Magnetometer

Wu¹,

Hu²,

Wu³

et al. 2013

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

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Abstract-Strapdownthree-axis magnetometer needs calibration before it can be properly employed for navigation purposes. Many scalar calibration methods have been proposed to determine the calibration parameters. However, most calibration approaches seldom describe the influence of sampling distributions on the parameters estimation. As a result, some approaches lack robustness when measurement points are not well distributed. This paper presents the usage of D-optimal design to improve the accuracy and robustness of the solutions for magnetometer calibration problem. The basic idea is to choose the measurement point positions to build a Doptimal design, and then seek optimal solutions of the cost function of the D-optimal design problem by using the particle swarm optimization (PSO) algorithm. Numerical results which show the large improvement in the accuracy and robustness of the solutions are achieved.

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Calibration methods for inertial and magnetic sensors

Cited by 157 publications

References 13 publications

A Particle Filter for Smartphone-Based Indoor Pedestrian Navigation

A Particle Filter for Smartphone-Based Indoor Pedestrian Navigation

Calibration of Miniature Inertial and Magnetic Sensor Units for Robust Attitude Estimation

D-Optimal Design Applied to Calibration of Strapdown Three-axis Magnetometer

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