Active magnetic detection is an effective method for detecting metal targets. Its practical application is confirmed in many previous studies, and its advantages over passive detection have been widely recognized. Most importantly, it can detect weak magnetic or nonmagnetic metal targets, unlike traditional magnetic detection. However, the secondary magnetic field generated by the eddy current on the target excited by the active emission primary magnetic field is always weak, and it has a fast attenuation in space. The target signal measured by the sensor is typically several orders of magnitude smaller than the background interference, which makes it challenging to extract the target signal during detection. This study mitigates these challenges by constructing the secondary magnetic field characteristic of the target from the perspective of signal energy. A set of 13 orthonormal basis functions (OBFs) are further derived to linearly describe this characteristic, which improves the signal-to-noise ratio (SNR) of the signal. The main contribution of this study is the proposal of an eddy current magnetic field OBF (ECMF-OBF) method to effectively characterize the secondary magnetic field of magnetic targets in active magnetic detection. The SNR is considerably improved by the proposed method, and this is independent of the target magnetic moment orientation. Our experiment is performed in different environments, including indoors, lake, and sea, to verify the method’s performance. Therefore, it has excellent value in the practical application of active magnetic detection.

To achieve high-precision vector measurement values in a geomagnetic field, it is necessary to develop methods for overcoming alternating magnetic interference (AMI), which is generated by electrical equipment. This paper proposes the adaptive alternating magnetic interference suppression (AAIS) algorithm. In this algorithm, first, only a triaxial fluxgate sensor measures the magnetic field data. The time–frequency diagram of the total magnetic field is obtained quickly through short-time Fourier transform and wavelet transform. Additionally, the time and frequency of AMI appearance are analyzed. Then, the triaxial adaptive notch filter suppresses the three-component related magnetic interference. Herein, simulation and actual experiments are performed to verify the effectiveness of AAIS. The results indicate that the algorithm can quickly detect the frequencies of AMI from the total magnetic field and adaptively fit their amplitude and phase on the vector magnetic field. Finally, AAIS can suppress the interference effectively. The AAIS algorithm realizes error compensation for the vector measurement values by the total magnetic field, which effectively improves the vector measurement accuracy of the geomagnetic field. We highlight that the AAIS algorithm is effective for AMIs of different frequencies, numbers, and intensities without reference sensors. Our work has practical implications in airborne, vehicle-mounted, and shipborne geomagnetic vector detection.