A High-Precision Magnetic Localization Method Based on EFLM for Attenuating Interference

• Published in: IEEE transactions on instrumentation and measurement Vol. 74; pp. 1 - 10
• Main Authors: Lv, Bowen, Dai, Houde, Qin, Yanding, Lin, Haijun
• Format: Journal Article
• Language: English
• Published: New York IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Background noise; Error fusion-based Levenberg-Marquardt (EFLM); impulse noise; Interference; Localization; Localization method; Location awareness; magnet localization; Magnetic field measurement; Magnetic fields; Magnetic flux; magnetic interference; Magnetic noise; Magnetic separation; Magnetic shielding; Magnetometers; Mathematical models; Medical instruments; Performance evaluation; permanent magnet; Real time; Root-mean-square errors; Standard deviation; Tracking systems
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2025.3558807

The potential of magnetic localization in a variety of applications is significant, including navigation for medical instruments, robotic localization, and indoor tracking systems, where accurate real-time localization is imperative. However, dynamic environmental noise, particularly from rapidly fluctuating magnetic fields, can severely degrade the performance of conventional localization algorithms, limiting their practical use. This article presents an error fusion-based Levenberg-Marquardt (EFLM) localization method designed to achieve robust magnetic tracking in environments subject to rapidly attenuated magnetic field disturbances. A detailed comparison was conducted between the EFLM algorithm and five state-of-the-art localization methods, to evaluate their performance under varying impulse noise conditions. In intense interference environments, the proposed EFLM algorithm demonstrates significant improvements over conventional LM method across 4800 dynamic localizations: the root-mean-squared error (RMSE) of position decreases by 48.4% (from 6.4 to 3.3 mm) with a 39.5% reduction in standard deviation (from 4.3 to 2.6 mm), while the RMSE of orientation drops by 62.5% (from 9.6° to 3.6°) with a 56.9% reduction in standard deviation (from 6.5° to 2.8°). These advancements are achieved while maintaining competitive computational efficiency, ensuring viability for real-time deployment.