ArticleSensors (Basel, Switzerland)2022
Effectiveness of Artificial Neural Networks for Solving Inverse Problems in Magnetic Field-Based Localization.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Millimeter-Scale Magnetic Positioning Using a Single AMR Sensor and BP Neural Network.Sensors (Basel, Switzerland) · 2026Article
- AI-Assisted Passive Magnetic Distance/Position Sensor.Sensors (Basel, Switzerland) · 2025Article
- Signal Processing and Machine Learning for Smart Sensing Applications.Sensors (Basel, Switzerland) · 2023Article
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1 author.
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Abstract
Recently, indoor localization has become an active area of research. Although there are various approaches to indoor localization, methods that utilize artificially generated magnetic fields from a target device are considered to be the best in terms of localization accuracy under non-line-of-sight conditions. In magnetic field-based localization, the target position must be calculated based on the magnetic field information detected by multiple sensors. The calculation process is equivalent to solving a nonlinear inverse problem. Recently, a machine-learning approach has been proposed to solve the inverse problem. Reportedly, adopting the
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