Motion Identification by Magnetic Anomaly Detection Employing a Fluxgate Crisscross Network : -2D Parameters Identification for Uniform Linear Motion

Magnetic anomaly detection (MAD) is a reliable tool for ferromagnetic objects detecting, even the hidden moving targets. In this paper, a novel method of two-dimension motion parameters identification by magnetic anomaly detection using a fluxgate crisscross network is proposed and implemented. The primarily achieved system consists of 13 single-axis fluxgates arranged as a crisscross network, and the magnetic parameters of each sensor are <; 5pT/√HZ@1HZ noise level, 0.5nT/hour stability and 1Hz bandwidth, and all sensors have self-balance and geomagnetic field compensation function. The primary results confirm the effectiveness of the magnetic anomaly detection system for motion parameters identification, especially the crisscross network structure and 2D parameter identification algorithm. For more precise identification, the replacement of fluxgate with much-higher-performance magnetometers such as SQUID and AM and increment of the sensors utilized can be helpful. This MAD system also has the potential to expand to 3D detection by structure and algorithm updating.