{"title":"Effect of sensor noise characteristics and calibration errors on the choice of IMU-sensor fusion algorithms","authors":"Aparna Harindranath, Manish Arora","doi":"10.1016/j.sna.2024.115850","DOIUrl":null,"url":null,"abstract":"<div><p>This paper focuses on accurate and precise orientation estimation with consumer-grade MEMS-IMUs for ‘slow’ orientation change and ‘short’-time applications. A simulation platform is developed to predict a suitable algorithm for a MEMS-IMU of known noise specifications, improving similar works. Experimentally measured noise characteristics of two commercial grade IMUs (MPU9250 and BNO055) are used in the simulation platform to generate simulated data and evaluate some popular orientation estimation algorithms along with two new Kalman filter-based algorithms. Real experiments are conducted with the same IMUs using an electromagnetic tracker as reference sensor. The output orientation results for two new improved algorithms are compared with other algorithms in simulations and real experiments. We show that the choice of the ‘best’ algorithm varies with the noise characteristics of individual sensors within the sensor module. The two new best-performing algorithms tested achieve<1˚ RMS angle error for the two low-cost consumer-grade IMUs.</p></div>","PeriodicalId":21689,"journal":{"name":"Sensors and Actuators A-physical","volume":"379 ","pages":"Article 115850"},"PeriodicalIF":4.1000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sensors and Actuators A-physical","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0924424724008446","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This paper focuses on accurate and precise orientation estimation with consumer-grade MEMS-IMUs for ‘slow’ orientation change and ‘short’-time applications. A simulation platform is developed to predict a suitable algorithm for a MEMS-IMU of known noise specifications, improving similar works. Experimentally measured noise characteristics of two commercial grade IMUs (MPU9250 and BNO055) are used in the simulation platform to generate simulated data and evaluate some popular orientation estimation algorithms along with two new Kalman filter-based algorithms. Real experiments are conducted with the same IMUs using an electromagnetic tracker as reference sensor. The output orientation results for two new improved algorithms are compared with other algorithms in simulations and real experiments. We show that the choice of the ‘best’ algorithm varies with the noise characteristics of individual sensors within the sensor module. The two new best-performing algorithms tested achieve<1˚ RMS angle error for the two low-cost consumer-grade IMUs.
期刊介绍:
Sensors and Actuators A: Physical brings together multidisciplinary interests in one journal entirely devoted to disseminating information on all aspects of research and development of solid-state devices for transducing physical signals. Sensors and Actuators A: Physical regularly publishes original papers, letters to the Editors and from time to time invited review articles within the following device areas:
• Fundamentals and Physics, such as: classification of effects, physical effects, measurement theory, modelling of sensors, measurement standards, measurement errors, units and constants, time and frequency measurement. Modeling papers should bring new modeling techniques to the field and be supported by experimental results.
• Materials and their Processing, such as: piezoelectric materials, polymers, metal oxides, III-V and II-VI semiconductors, thick and thin films, optical glass fibres, amorphous, polycrystalline and monocrystalline silicon.
• Optoelectronic sensors, such as: photovoltaic diodes, photoconductors, photodiodes, phototransistors, positron-sensitive photodetectors, optoisolators, photodiode arrays, charge-coupled devices, light-emitting diodes, injection lasers and liquid-crystal displays.
• Mechanical sensors, such as: metallic, thin-film and semiconductor strain gauges, diffused silicon pressure sensors, silicon accelerometers, solid-state displacement transducers, piezo junction devices, piezoelectric field-effect transducers (PiFETs), tunnel-diode strain sensors, surface acoustic wave devices, silicon micromechanical switches, solid-state flow meters and electronic flow controllers.
Etc...