An Approach for Observing and Modeling Errors in MEMS-Based Inertial Sensors Under Vehicle Dynamic

Stebler, Yannick; Guerrier, Stéphane; Skaloud, Jan

doi:10.1109/tim.2015.2444239

Cited by 25 publications

(11 citation statements)

References 16 publications

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“…The fixed parameters (i.e., the constant components of the scale factors) and bias vector components were estimated with a classical least-squares parametric compensation. The remaining parameters were estimated with variance analysis techniques, as explained in [30] and [55].…”

Section: Skewed-redundant Magnetometer Fusionmentioning

confidence: 99%

Skewed-redundant Hall-effect Magnetic Sensor Fusion for Perturbation-free Indoor Heading Estimation

Karimi¹,

Babaians²,

Oelsch³

et al. 2020

Preprint

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Robust attitude and heading estimation with respect to a known reference is an essential component for indoor localization in robotic applications. Affordable Attitude and Heading Reference Systems (AHRS) are typically using 9-axis solid-state MEMS-based sensors. The accuracy of heading estimation on such a system depends on the Earth's magnetic field measurement accuracy. The measurement of the Earth's magnetic field using MEMS-based magnetometer sensors in an indoor environment, however, is strongly affected by external magnetic perturbations. This paper presents a novel approach for robust indoor heading estimation based on skewed-redundant magnetometer fusion. A tetrahedron platform based on Hall-effect magnetic sensors is designed to determine the Earth's magnetic field with the ability to compensate for external magnetic field anomalies. Additionally, a correlation-based fusion technique is introduced for perturbation mitigation using the proposed skewed-redundant configuration. The proposed fusion technique uses a correlation coefficient analysis for determining the distorted axis and extracts the perturbation-free Earth's magnetic field vector from the redundant magnetic measurement. Our experimental results show that the proposed scheme is able to successfully mitigate the anomalies in the magnetic field measurement and estimates the Earth's true magnetic field. Using the proposed platform, we achieve a Root Mean Square Error of 12.74$\degree$ for indoor heading estimation without using an additional gyroscope.

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Section: Skewed-redundant Magnetometer Fusionmentioning

confidence: 99%

Skewed-redundant Hall-effect Magnetic Sensor Fusion for Perturbation-free Indoor Heading Estimation

Karimi¹,

Babaians²,

Oelsch³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Therefore, sophisticated wavelet denoising method is applied to attenuate both wide band frequency noises as well as the noises falling within bandwidth (Abd-Elhamid et al, 2005; El-Sheimy et al, 2004). Under highly dynamic environmental conditions, such as in-flight, vehicle or underwater, advanced translation invariant wavelet (TIW) transform is implemented by researchers to perform cascade denoising (Chiang et al, 2004; Stebler et al, 2015). Designing an optimal denoising that can work in changing operational conditions is quite challenging; hence, non-conventional methods such as neural network and fuzzy logic are also reported in the literature to make denoising adaptive (Baselga et al, 2009; El-Rabbany et al, 2004; Liu and Zhu, 2016).…”

Section: Noises In Mems Inertial Measurementmentioning

confidence: 99%

Errors in micro-electro-mechanical systems inertial measurement and a review on present practices of error modelling

Bhardwaj

Kumar

2017

Transactions of the Institute of Measurement and Control

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Micro-electro-mechanical systems (MEMS) technology-based accelerometers and gyroscopes are small size, mass produced, low cost inertial sensors, which are now being used in aerospace, underwater vehicles, automotive, robotics, mobiles, gaming consoles, prosthetic devices and many other applications. MEMS inertial sensors are available in many grades in market and selecting the appropriate grade sensor is very important. Owing to interaction of different types of energies, different noises are generated in MEMS devices; these noises cause significant change in output and the first section of this paper illustrates that. In application, where MEMS inertial sensors are used, the accuracy, repeatability and reproducibility of inertia measurement is probed primarily by complex testing, using extensive range of physical stimuli. Noises in inertial measurement are generally dealt by designing a unit measurement model. Noises are treated as additive error in linear unit model and are modelled using various techniques so that errors can be compensated to improve the accuracy. This paper reviews the theory, framework and methodology used in the error model of a MEMS inertial sensor and stochastic modelling of measurement. Experimental results from the most commonly used Allan variance techniques are discussed. Error modelling methodology, consisting of testing and calibration methods, designing thermal model, stochastic modelling and parameter estimation techniques, is illustrated. Figures and tables under each section summarize features, merits, limitation and future research scope. This paper should serve as a single reference for researchers and engineers working on application specific system design and instrumentation using MEMS inertial sensors. Conclusion from the study should help in selecting the appropriate grade of sensor as well as the best error modelling as per the trade-off existing between accuracy and development cost of error modelling.

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“…Earth rotation projections onto NED axis is shown in (7) where angular velocity of the earth rotation  e = 7.292115 × 10 -5 rad/s, which can be neglected for short navigation with low performance sensors. Angular velocity of rotation of a navigation coordinate frame relative to the earth is shown in (8). Position coordinates longitude, latitude, height are λ, , h respectively and R M , R p are radius of curvature along Earths meridian and parallel.…”

Section:  mentioning

confidence: 99%

“…Proper crash test recording thus requires specially designed components [7]. More recent work [8], [9] studies behavior of low-cost inertial micro-electro mechanical sensors (MEMS) in dynamic conditions. One of the findings is that characteristics of the rate gyroscopes are more stable than of the accelerometers.…”

Section: Introductionmentioning

confidence: 99%

Experimental Verification of Inertial Navigation with MEMS for Forensic Investigation of Vehicle Collision

Tadic¹,

Vukajlovic²

2016

RADIOENGINEERING

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An Approach for Observing and Modeling Errors in MEMS-Based Inertial Sensors Under Vehicle Dynamic

Cited by 25 publications

References 16 publications

Skewed-redundant Hall-effect Magnetic Sensor Fusion for Perturbation-free Indoor Heading Estimation

Skewed-redundant Hall-effect Magnetic Sensor Fusion for Perturbation-free Indoor Heading Estimation

Errors in micro-electro-mechanical systems inertial measurement and a review on present practices of error modelling

Experimental Verification of Inertial Navigation with MEMS for Forensic Investigation of Vehicle Collision

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