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A Comprehensive Analysis of Magnetic Field Based Indoor Positioning With Smartphones: Opportunities, Challenges and Practical Limitations.

, , , and . IEEE Access, (2020)

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Analysis on the characteristics of mutual interference between pulsed terrestrial LIDAR scanners., , , and . IGARSS, page 2151-2154. IEEE, (2015)Wi-Fi-Based Effortless Indoor Positioning System Using IoT Sensors., , and . Sensors, 19 (7): 1496 (2019)An Efficient Addressing Scheme and Its Routing Algorithm for a Large-Scale Wireless Sensor Network., , , and . EURASIP J. Wireless Comm. and Networking, (2008)Floor Identification Using Magnetic Field Data with Smartphone Sensors., , , and . Sensors, 19 (11): 2538 (2019)Cloudlet Federation Based Context-Aware Federated Learning Approach., , , , , , and . IEEE Access, (2022)MagWi: Benchmark Dataset for Long Term Magnetic Field and Wi-Fi Data Involving Heterogeneous Smartphones, Multiple Orientations, Spatial Diversity and Multi-Floor Buildings., , , , , and . IEEE Access, (2021)Localizing pedestrians in indoor environments using magnetic field data with term frequency paradigm and deep neural networks., , , , , and . Int. J. Mach. Learn. Cybern., 12 (11): 3203-3219 (2021)LOCALI: Calibration-Free Systematic Localization Approach for Indoor Positioning., , and . Sensors, 17 (6): 1213 (2017)Low complexity LTS-based NLOS error mitigation for localization., , and . Ann. des Télécommunications, 67 (9-10): 471-476 (2012)Map Building Based on Sensor Fusion for Autonomous Vehicle., , , and . ITNG, page 490-495. IEEE Computer Society, (2014)