Dynamic Adjustment of Measurement Noise Covariance Matrix in an Infrared-based Positioning and Tracking System
Authors
Aparicio Esteve, Elena; Moltó Orozco, David; Ureña Ureña, Jesús; Hernández Alonso, Álvaro; Espinosa Zapata, FelipeIdentifiers
Permanent link (URI): http://hdl.handle.net/10017/57897DOI: 10.1109/IPIN54987.2022.9917511
ISBN: 978-1-7281-6218-8
Publisher
IEEE
Date
2022-10-26Funders
Agencia Estatal de Investigación
Universidad de Alcalá
Bibliographic citation
Aparicio Esteve, E., Moltó, D., Ureña, J., Hernández, Á. & Espinosa, F. 2022, "Dynamic Adjustment of Measurement Noise Covariance Matrix in an Infrared-based Positioning and Tracking System”, in 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 1-8. DOI: 10.1109/IPIN54987.2022.9917511.
Keywords
Local Positioning System
Infrared
EKF
Description / Notes
2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN), 5-8 September, 2022, Beijing, China.
Project
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095168-B-C51/ES/SISTEMAS DE POSICIONAMIENTO LOCAL: ENFOQUE HOLISTICO DESDE LAS TECNOLOGIAS BASE HASTA LAS APLICACIONES/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105470RA-C33/ES/MEJORANDO Y FOMENTANDO LA VIDA ACTIVA Y BIENESTAR DE LAS PERSONAS CON DEMENCIA Y DETERIORO COGNITIVO LEVE MEDIANTE EL USO DE TECNICAS DE LOCALIZACION/
info:eu-repo/grantAgreement/UAH//CM-JIN-2021-027
info:eu-repo/grantAgreement/UAH//CM-JIN-2021-016
Document type
info:eu-repo/semantics/bookPart
Version
info:eu-repo/semantics/acceptedVersion
Publisher's version
https://doi.org/10.1109/IPIN54987.2022.9917511Rights
Attribution-NonCommercial-NoDerivatives 4.0 International (CC-BY-NC-ND 4.0)
© 2022 IEEE
Access rights
info:eu-repo/semantics/openAccess
Abstract
The accuracy of optical positioning systems can be compromised by multiple factors (reflections, calibration, etc.). As an alternative to the triangulation, multilateration, or fingerprinting techniques typically used in these systems, stochastic estimation techniques can be used, such as Kalman Filters (KF) in its different variants. They estimate the receiver position based on the acquired measurements and the estimated positions in previous iterations. This work presents the evaluation of a 3D optical positioning system, based on four LED beacons and a quadrant receiver, using an Extended Kalman Filter (EKF). The implementation of a measurement noise covariance matrix that is adjusted depending on the angle and distance between transmitters and receiver, obtained in the previous iteration, is analysed. The receiver position estimation using both a dynamic and a static measurement noise covariance matrix is evaluated and compared with simulations and experimental tests. In simulations, the achieved errors are below 6 cm and 12 cm in 75% of the cases when using a dynamic and a static noise matrix, respectively. In the experimental tests, the obtained errors in 75% of the cases for the position in plane XY and the rotation angle ? are smaller than 7.44 cm and 1.06 ? with a dynamic noise matrix; and below 7.59 cm and 1.62 ? for a static one.
Files in this item
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Dynamic_Aparicio_IEEE_IPIN_2022.pdf | 1.233Mb |
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Dynamic_Aparicio_IEEE_IPIN_2022.pdf | 1.233Mb |
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