Inertial sensor signals denoising with directed transfer function

Edu, Ioana Raluca; Grigorie, Teodor Lucian; Adochiei, Felix-Constantin; Rotaru, Constantin; Jula, Nicolae

doi:10.1109/atee.2015.7133938

Cited by 6 publications

(5 citation statements)

References 4 publications

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“…In order to achieve precise and realistic results in a comprehensive study that mirrors the actual conditions of the navigation system, including the inherent errors of the sensors employed, it becomes imperative to establish an equivalent model. To create the software representation of an IMU, the process was initiated by implementing an accelerometer and a gyro in MATLAB/Simulink using IEEE standardized models [3,14].…”

Section: Software Configuration Of the Mems-based Imu And Wavelet Fil...mentioning

confidence: 99%

“…Instead of a continuous and clear evolution representation of the measured dataset, the useful signal is often submerged in the noise. Conventional filtering methods usually prove to be inefficient and may even cause signal distortion due to the tendency of noise frequency bands to overlap with the frequency band in which the dynamics of the monitored vehicle are located [3].…”

Section: Introductionmentioning

confidence: 99%

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Improvement of the global positioning accuracy with miniaturized strap-down INS systems through wavelet filtering of data from MEMS inertial sensors

Antofie,

Larco,

Lucian Grigorie

2023

Modern Applications of Wavelet Transform

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In this chapter, the correlation between the issue of perturbed data acquired from miniaturized inertial sensors and the wavelet filtering technique is investigated. The market growth of micro-electro-mechanical systems (MEMS) has impacted various fields, and its potential application in strap-down inertial navigation systems (INS) could not be overlooked. Despite the apparent benefits of dimension and price reduction, the utilization of miniaturized inertial sensors for manufacturing the inertial measurement unit (IMU) entails certain drawbacks: the output signals are usually corrupted with different types of errors, which distort the real navigation information. The proposed case focuses on the suitability of wavelets for denoising the perturbed IMU signals before being erroneously processed by the navigation algorithm. The applicative part consisted in implementing sensor software models in Simulink and testing various wavelet filters. Furthermore, to fully assess the efficacy of the wavelet denoising technique, the model of a SDINS employing a MEMS-based IMU was established in Simulink. The evaluation involved comparing the attitude, position and speed components obtained before and after the denoising procedure with those of an ideal model linked to constant inputs. The results demonstrated the effectiveness of the proposed association in terms of positioning accuracy, signal characteristics improvement and computation complexity.

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Section: Software Configuration Of the Mems-based Imu And Wavelet Fil...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improvement of the global positioning accuracy with miniaturized strap-down INS systems through wavelet filtering of data from MEMS inertial sensors

Antofie,

Larco,

Lucian Grigorie

2023

Modern Applications of Wavelet Transform

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“…Starting from a new time frequency approach for assessing coupling dynamics information in multivariate dynamic systems [4] we proposed a new method for estimating the optimal decomposition level of the wavelet filter.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…This noise component that overlaps over the useful output of the sensors cannot be totally eliminated but can be modelled by using stochastic processes [4].…”

Section: Incas Bulletin Volume 7 Issue 1/ 2015mentioning

confidence: 99%

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Inertial Sensor Signals Denoising with Wavelet Transform

Edu¹,

Felix-Constantin²,

Obreja³

et al. 2015

INCAS BULLETIN

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Abstract:In the current paper we propose a new software procedure for processing data from an inertial navigation system boarded on a moving vehicle, in order to achieve accurate navigation information on the displacement of the vehicle in terms of position, speed, acceleration and direction. We divided our research in three phases. In the first phase of our research, we implemented a realtime evaluation criterion with the intention of achieving real-time data from an accelerometer. It is well-known that most errors in the detection of position, velocity and attitude in inertial navigation

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