Test and error parameter estimation for MEMS — based low cost IMU calibration

Lee, Dongkyu; Lee, Sangchul; Park, Sanghyuk; Ko, Sangho

doi:10.1007/s12541-011-0077-9

Cited by 42 publications

(28 citation statements)

References 14 publications

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“…The frequency-domain representation allows us to observe some errors in IMU data, as presented in [46], where Fourier Transform (FT) is used to estimate parameters such as, bias, scale factor, and misalignment of the accelerometers and rate gyros. As an example, the bias component can be found at the 0 Hz value of the FT.…”

Section: Sensor and Scenario Analysismentioning

confidence: 99%

Context-Aided Sensor Fusion for Enhanced Urban Navigation

Martí

Martín

García

et al. 2012

Sensors

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The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments.

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Section: Sensor and Scenario Analysismentioning

confidence: 99%

Context-Aided Sensor Fusion for Enhanced Urban Navigation

Martí

Martín

García

et al. 2012

Sensors

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“…Digital magnetometers, pressure sensor, or some other sensors are integrated on them. Therefore, the whole performance has greatly enhanced and the aforementioned MIMU have the advantages of light weight, small size, low cost, high reliability, and long lifespan [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…Before implementing the calibration, the calibration model should be established. As shown in the literature, the calibration model is usually established based on the bias errors, the scale factor errors, the installation errors, and some other related parameters [5,[7][8][9]. By means of the calibration, all parameters in the calibration model can be obtained.…”

Section: Introductionmentioning

confidence: 99%

Research on the Calibration Method of Micro Inertial Measurement Unit for Engineering Application

Yang¹,

Wang²,

Su³

2016

Journal of Sensors

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With rapid development of micro fabrication technology, the production level of micro inertial devices has increased, which promoted the performance improvement of Micro Inertial Measurement Unit (MIMU). Measurement precision of MIMU is one of the most significant indexes, especially for the application of the guided spinning projectiles. In order to improve the measurement precision of MIMU, this paper presents a novel calibration method. The calibration model is established and the derivation for parameters estimation has been introduced. By the multirate tests and multiposition tests, all the parameters in the calibration model can be well estimated. Verification experiment shows that the proposed method has the same compensation effect as the traditional method, but it can alleviate the computing burden for the system. Thus the proposed method will have a wide application prospect for the future engineering calibration.

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“…On the one hand, devices like e.g., dron-type aerial vehicles driven by quadrorotors sometimes require application of a state-of-art IMU (e.g., while keeping a stabilized position over a long term). Such unit is described e.g., by Lee et al, 2 focusing on improvement of its metrological parameters owing to a novel calibration procedure proposed. On the other hand, there exist many devices that employ very simple tilt measurements (e.g., landscape or portrait orientation of a picture in a cellular telephone), where application of MEMS accelerometers is possible without any sophisticated signal processing.…”

Section: Introductionmentioning

confidence: 99%

Erratum to: Guidelines for tilt measurements realized by MEMS accelerometers

Łuczak

2014

Int. J. Precis. Eng. Manuf.

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The paper discusses thoroughly a problem of determining tilt over various measurement ranges by measuring Cartesian components of the gravity acceleration with application of accelerometers that are Microelectromechanical Systems (MEMS). The presented standard and original methods are based on various mathematical relationships between the components and the pitch and the roll. Their application results in the fact that the realized measurements are characterized by different sensitivity and accuracy (experimentally evaluated to be of 0.18 o-2 o for a tilt sensor built of standard MEMS accelerometers). Each method is discussed in detail with regard to the respective sensitivity and accuracy of the measurement, and its application scope is determined. Essential part of the paper are guidelines for an optimal selection of the number and type of MEMS accelerometers, as well as appropriate mathematical formula, to be used in a specific case of tilt measurement.

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Test and error parameter estimation for MEMS — based low cost IMU calibration

Cited by 42 publications

References 14 publications

Context-Aided Sensor Fusion for Enhanced Urban Navigation

Context-Aided Sensor Fusion for Enhanced Urban Navigation

Research on the Calibration Method of Micro Inertial Measurement Unit for Engineering Application

Erratum to: Guidelines for tilt measurements realized by MEMS accelerometers

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