Calibration Optimization Study for Tilt-Compensated Compasses

Gheorghe, Marius V.; Bodea, Mircea

doi:10.1109/tim.2018.2795278

Cited by 16 publications

(6 citation statements)

References 18 publications

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“…Today, this typically involves the simultaneous deployment of tri-axial accelerometers and magnetometers [e.g., 6,7,13,[14][15][16][17], utilising the tilt-compensated compass method [cf. 18,[19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Dead-Reckoning Animal Movements in R – A Reappraisal Using Gundog.Tracks

Gunner

Holton

Scantlebury

et al. 2021

Preprint

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Background Fine-scale data on animal position are increasingly enabling us to understand the details of animal movement ecology and dead-reckoning, a technique integrating motion sensor-derived information on heading and speed, can be used to reconstruct fine-scale movement paths at sub-second resolution, irrespective of the environment. On its own however, the dead-reckoning process is prone to cumulative errors, so that position estimates quickly become uncoupled from true location. Periodic ground-truthing with aligned location data (e.g., from global positioning technology) can correct for this drift between Verified Positions (VPs). Yet relatively few bio-logging studies have adopted this approach due to an apparent inaccessibility of the complex analytical processes involved. We present step-by-step instructions for implementing Verified Position Correction (VPC) dead-reckoning in R using the tilt-compensated compass method, accompanied by the mathematical protocols underlying the code and improvements and extensions of this technique to reduce the trade-off between VPC rate and dead-reckoning accuracy. These protocols are all built into a user-friendly, fully-annotated VPC dead-reckoning R function; Gundog.Tracks, with multi-functionality to reconstruct animal movement paths across terrestrial, aquatic, and aerial systems, provided within the supplementary information as well as online (GitHub). Results The Gundog.Tracks function is demonstrated on three contrasting model species (the African lion Panthera leo, the Magellanic penguin Spheniscus magellanicus, and the Imperial cormorant Leucocarbo atriceps) moving on land, in water and in air, respectively. We show the effect of uncorrected errors in speed estimations, heading inaccuracies and infrequent VPC rate and demonstrate how these issues can be addressed. Conclusions The function provided will allow anyone familiar with R to dead-reckon animal tracks readily and accurately, as the key complex issues are dealt with by Gundog.Tracks. This will help the community to consider and implement a valuable, but often overlooked method of reconstructing high-resolution animal movement paths across diverse species and systems without requiring a bespoke application.

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Section: Introductionmentioning

confidence: 99%

Dead-Reckoning Animal Movements in R – A Reappraisal Using Gundog.Tracks

Gunner

Holton

Scantlebury

et al. 2021

Preprint

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“…It has been proved that this constraint problem has a unique solution in the field of mathematics [ 38 ]. Therefore, the ellipsoid coefficient vector can be determined, and then the ellipsoid radius and the nonorthogonal error angle can be calculated based on the ellipsoid coefficient.…”

Section: Methodsmentioning

confidence: 99%

“…Moreover, in practice, the measurement error of MEMS magnetometer is non-negligible, the magnetometer measurement error mainly includes environmental interference and inherent error [ 12 , 37 ]. Researchers have conducted various calibration methods using high precision instruments and equipments [ 38 , 43 , 44 ], however, these methods are time-consuming and the calibration effect largely relies on the precision of equipment. This work uses a calibration method which allows non-experts to easily implement the calibration procedure.…”

Section: Methodsmentioning

confidence: 99%

MEMS Inertial Sensors Based Gait Analysis for Rehabilitation Assessment via Multi-Sensor Fusion

et al. 2018

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Gait and posture are regular activities which are fully controlled by the sensorimotor cortex. In this study, fluctuations of joint angle and asymmetry of foot elevation in human walking stride records are analyzed to assess gait in healthy adults and patients affected with gait disorders. This paper aims to build a low-cost, intelligent and lightweight wearable gait analysis platform based on the emerging body sensor networks, which can be used for rehabilitation assessment of patients with gait impairments. A calibration method for accelerometer and magnetometer was proposed to deal with ubiquitous orthoronal error and magnetic disturbance. Proportional integral controller based complementary filter and error correction of gait parameters have been defined with a multi-sensor data fusion algorithm. The purpose of the current work is to investigate the effectiveness of obtained gait data in differentiating healthy subjects and patients with gait impairments. Preliminary clinical gait experiments results showed that the proposed system can be effective in auxiliary diagnosis and rehabilitation plan formulation compared to existing methods, which indicated that the proposed method has great potential as an auxiliary for medical rehabilitation assessment.

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“…When tilting a magnetic compass in any direction, observation shows that the shape of trajectory derived from orthogonal tri-axis outputs with respect to carrier coordinate reference maintains a normal sphere, which is characterized by the hypothesis that the magnetic compass is working in a pure geomagnetic environment without any interference like hard or soft iron on the host platform [ 17 , 18 ]. In practice, however, even though the intrinsic instrumentation errors of the magnetic compass, for example, scale factors, non-orthogonality, and offsets, exert certain influences on measuring results, we concentrate more upon eliminating the impacts of environmental magnetic field interferences, because in cases where hard or soft iron exists, we can only obtain an irregular ellipsoid rather than an approximate normal sphere [ 19 , 20 , 21 ]. The following subsections describe the elaborate tri-axis distribution transformation by mathematical means.…”

Section: Two-step Optimized Magnetic Coefficients Correction Algormentioning

confidence: 99%

An Optimized Two-Step Magnetic Correction Strategy by Means of a Lagrange Multiplier Estimator with an Ellipsoid Constraint

Xia

Geng

Yang

et al. 2018

Sensors

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The geomagnetic field is as fundamental a constituent of passive navigation as Earth’s gravity. In cases where no other external attitude reference is available, for the direct heading angle estimation by a typical magnetic compass, a two-step optimized correction algorithm is proposed to correct the model coefficients caused by hard and soft iron nearby. Specifically, in Step 1, a Levenberg-Marquardt (L-M) fitting estimator with an ellipsoid constraint is applied to solve the hard magnetic coefficients. In Step 2, a Lagrange multiplier estimator is used to deal with the soft magnetic iron circumstance. The essential attribute of “the two-step” lies in its eliminating the coupling effects of hard and soft magnetic fields, and their mutual interferences on the pure geomagnetic field. Under the conditions of non-deterministic magnetic interference sources with noise, the numerical simulation by referring to International Geomagnetic Reference Field (IGRF), and the laboratory tests based upon the turntable experiments with Honeywell HMR3000 compass (Honeywell, Morristown, NJ, USA) conducted, the experimental results indicate that, in the presence of the variation of multi-magnetic interferences, the RMSE (Root Mean Square Error) value of the estimated total magnetic flux density by the proposed two-step estimator falls to 0.125 μT from its initial 2.503 μT, and the mean values of the heading angle error estimates are less than 1°. The proposed solution therefore, exhibits ideal convergent properties, fairly meeting the accuracy requirements of non-tactical level navigation applications.

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Calibration Optimization Study for Tilt-Compensated Compasses

Cited by 16 publications

References 18 publications

Dead-Reckoning Animal Movements in R – A Reappraisal Using Gundog.Tracks

Dead-Reckoning Animal Movements in R – A Reappraisal Using Gundog.Tracks

MEMS Inertial Sensors Based Gait Analysis for Rehabilitation Assessment via Multi-Sensor Fusion

An Optimized Two-Step Magnetic Correction Strategy by Means of a Lagrange Multiplier Estimator with an Ellipsoid Constraint

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