Papers
2
Total Citations
13
H-Index
2
About
Yijie Qin is a researcher specializing in magnetic sensing, target detection, and localization technologies, with a focus on advancing magnetometer arrays and eddy current-based methods. Their major contributions include developing a calibration method for mismatch errors in magnetometer arrays using two excitation coils and the particle swarm optimization algorithm, which enhances the accuracy of ferromagnetic target tracking and magnetic anomaly detection in challenging environments. This work, cited 10 times, addresses critical challenges in suppressing background magnetic field interference. Qin also introduced an eddy current magnetic localization approach for nonmagnetic metal targets, based on a metal shell model, enabling precise detection of weakly magnetic or nonmagnetic objects—a breakthrough with applications in geological prospecting, medical monitoring, and disaster rescue. With a growing citation impact, Qin’s research bridges theoretical modeling and practical sensor calibration, offering robust solutions for real-world magnetic field sensing. Their work stands out for its innovative use of optimization algorithms and physical modeling, positioning them as a rising contributor to the field of magnetic anomaly detection and localization.
Research Focus
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Top Papers
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