High-precision indoor localization using the extended Kalman filter approach

Mohammad AlShabi; S. Andrew Gadsden; Khaled Obaideen; Talal Bonny

doi:10.1117/12.3015941

5 June 2024 High-precision indoor localization using the extended Kalman filter approach

Mohammad AlShabi, S. Andrew Gadsden, Khaled Obaideen, Talal Bonny

Proceedings Volume 13049, Laser Radar Technology and Applications XXIX; 130490O (2024) https://doi.org/10.1117/12.3015941
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Conference Poster

Abstract

Indoor positioning and navigation have emerged as critical areas of research due to the limitations of GPS in enclosed environments. This study presents an innovative approach to high-precision indoor localization by employing the Extended Kalman Filter (EKF). Unlike traditional methods that often suffer from noise and multi-path effects, the EKF methodology accounts for nonlinearities and offers a recursive solution to estimate the state of dynamic systems. We deployed a sensor on a mobile robot that needs to move in an indoor environment while there is a moving obstacle that is moving around. Our findings demonstrate a significant accuracy in locating the obstacle while maneuvering inside the environment.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mohammad AlShabi, S. Andrew Gadsden, Khaled Obaideen, and Talal Bonny "High-precision indoor localization using the extended Kalman filter approach", Proc. SPIE 13049, Laser Radar Technology and Applications XXIX, 130490O (5 June 2024); https://doi.org/10.1117/12.3015941

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