Accelerometer Calibration and Dynamic Bias and Gravity Estimation: Analysis, Design, and Experimental Evaluation

Batista, Pedro; Silvestre, Carlos; Oliveira, Paulo; Cardeira, B.

doi:10.1109/tcst.2010.2076321

Cited by 71 publications

(46 citation statements)

References 13 publications

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“…These studies used only a few models in controlled environments, and there was no corresponding evaluation in large-scale real-world applications. Researchers have also investigated sensor calibration in mobile devices, such as a time-varying Kalman filtering calibration technique to reduce sensor biases [2] and a machine learning based multiposition calibration scheme to address hardware heterogeneity in mobile devices [10]. In our work, using the large-scale real-world data collected via MyShake, we will evaluate sensing quality in terms of measuring ground motion, and further leverage/develop sensor calibration techniques to improve sensing quality and earthquake detection accuracy.…”

Section: Related Workmentioning

confidence: 99%

Earthquake Early Warning and Beyond

Kong

Allen

2019

Proceedings of the 20th International Workshop on Mobile Computing Systems and Applications

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Earthquake Early Warning (EEW) systems can effectively reduce fatalities, injuries, and damages caused by earthquakes. Current EEW systems are mostly based on traditional seismic and geodetic networks, and exist only in a few countries due to the high cost of installing and maintaining such systems. The MyShake system takes a different approach and turns people's smartphones into portable seismic sensors to detect earthquake-like motions. However, to issue EEW messages with high accuracy and low latency in the real world, we need to address a number of challenges related to mobile computing. In this paper, we first summarize our experience building and deploying the MyShake system, then focus on two key challenges for smartphone-based EEW (sensing heterogeneity and user/system dynamics) and some preliminary exploration. We also discuss other challenges and new research directions associated with smartphone-based seismic network. CCS CONCEPTS• Human-centered computing → Ubiquitous and mobile computing systems and tools; • Applied computing → Earth and atmospheric sciences.

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Section: Related Workmentioning

confidence: 99%

Earthquake Early Warning and Beyond

Kong

Allen

2019

Proceedings of the 20th International Workshop on Mobile Computing Systems and Applications

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“…For LTV systems a wide range of Kalman-related results are available; VOLUME 4, 2016 see [19], [20], and [21]. The solution in [22], with the state vector extended by ω and b ω , is chosen to solve the estimation problem. An aspect of (30b) is that it holds two competing integrators in b l and g. In [12], the subsystem (30a)-(30d) is found uniformly completely observable iff ω(t) has sufficient perturbations (with y = p v ).…”

Section: State Observermentioning

confidence: 99%

Disturbance Rejection by Acceleration Feedforward for Marine Surface Vessels

Kjerstad

Skjetne

2016

IEEE Access

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Acceleration signals have a powerful disturbance rejection potential in rigid body motion control, as they carry a measure proportional to the resulting force. Yet, they are seldom used, since measuring, decoupling, and utilizing the dynamic acceleration in the control design is not trivial. This paper discusses these topics and presents a solution for marine vessels building on conventional methods together with a novel control law design, where the dynamic acceleration signals are used to form a dynamic referenceless disturbance feedforward compensation. This replaces conventional integral action and enables unmeasured external loads and unmodel dynamics to be counteracted with low time lag. A case study shows the feasibility of the proposed design using experimental data and closed-loop high fidelity simulations of dynamic positioning in a harsh cold climate environment with sea-ice. INDEX TERMSMarine technology, Closed loop systems, Ice.

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“…The tri-axial accelerometer calibration procedure we adopted is similar to that described in [9], [10], but does not require any additional hardware (besides the IMU itself). It relies on the SEM (assuming a still sensor) [9], [10]…”

Section: Imu Description and Calibrationmentioning

confidence: 99%

Design and implementation of an inertial navigation system for pedestrians based on a low-cost MEMS IMU

Montorsi

Pancaldi

Vitetta

2013

2013 IEEE International Conference on Communications Workshops (ICC)

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Abstract-Inertial navigation systems for pedestrians are infrastructure-less and can achieve sub-meter accuracy in the short/medium period. However, when low-cost inertial measurement units (IMU) are employed for their implementation, they suffer from a slowly growing drift between the true pedestrian position and the corresponding estimated position. In this paper we illustrate a novel solution to mitigate such a drift by: a) using only accelerometer and gyroscope measurements (no magnetometers required); b) including the sensor error model parameters in the state vector of an extended Kalman filter; c) adopting a novel soft heuristic for foot stance detection and for zero-velocity updates. Experimental results evidence that our inertial-only navigation system can achieve similar or better performance with respect to pedestrian dead-reckoning systems presented in related studies, although the adopted IMU is less accurate than more expensive counterparts.

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Accelerometer Calibration and Dynamic Bias and Gravity Estimation: Analysis, Design, and Experimental Evaluation

Cited by 71 publications

References 13 publications

Earthquake Early Warning and Beyond

Earthquake Early Warning and Beyond

Disturbance Rejection by Acceleration Feedforward for Marine Surface Vessels

Design and implementation of an inertial navigation system for pedestrians based on a low-cost MEMS IMU

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