Correction Method of Three-Axis Magnetic Sensor Based on DA–LM

The fluxgate magnetometer has the advantages of having a small volume and low power consumption and being light weight and is commonly used to detect weak magnetic targets, including ferrous metals, unexploded bombs (UXOs), and underground corrosion pipelines. However, the detection accuracy of the fluxgate magnetometer is affected by its own error. To obtain more accurate detection data, the sensor must be error-corrected before application. Previous researchers easily fell into the local minimum when solving error parameters. In this paper, the error correction method was proposed to tackle the problem, which combines the Dragonfly algorithm (DA) and the Levenberg–Marquardt (LM) algorithm, thereby solving the problem of the LM algorithm and improving the accuracy of solving error parameters. Firstly, we analyzed the error sources of the three-axis magnetic sensor and established the error model. Then, the error parameters were solved by using the LM algorithm and DA–LM algorithm, respectively. In addition, by comparing the results of the two methods, we found that the error parameters solved by using the DA–LM algorithm were more accurate. Finally, the magnetic measurement data were corrected. The simulation results show that the DA–LM algorithm can accurately solve the error parameters of the triaxial magnetic sensor, proving the effectiveness of the proposed algorithm. The experimental results show that the difference between the corrected and the ideal total value was decreased from 300 nT to 5 nT, which further verified the effectiveness of the DA–LM algorithm.