Adaptive Magnetic Disturbance Suppression of a Shaking Buoy and Magnetic Anomaly Detection

The magnetic field characteristics play a crucial role in ship targeting, and magnetic anomaly detection is widely used for this purpose. Among the various applications, the utilization of sea surface buoys stands out. However, these buoys experience vigorous swaying due to sea wave fluctuations, resulting in substantial noise and a low signal-to-noise ratio (SNR) in the collected data. Consequently, the performance of magnetic anomaly detection suffers, hindering effective identification of the magnetic field signal from the target. To mitigate this challenge, we propose an adaptive method based on variable-step-size normalized least mean square (NLMS) with three magnetic field components as inputs. This method demonstrates rapid convergence, robust stability, real-time noise reduction caused by buoy platform motion, and independence from platform attitude information. Notably, it effectively suppresses the total magnetic field noise induced by the swaying of shallow-sea buoy platforms, thereby enhancing the SNR of the acquired signals. Experimental results reveal that our approach can highlight the magnetic flux curve of naval targets originally submerged in noise, achieving an adaptive gain of 44.69 dB. Ultimately, this method addresses the performance degradation issue in magnetic anomaly detection devices arising from noise interference due to buoy platform oscillations.