Wang Luo

Transient electromagnetics is an efficient technique for acquiring subsurface resistivity, and its system mainly consists of a transmitter that induces eddy currents in the ground and a receiver that detects the resulting induced magnetic field subsequently. The strict time synchronization between the transmitter and receiver constrains the interoperability within different systems. To address this compatibility barrier, this paper proposes a universal self-synchronizing receiver with the ability to trigger itself by utilizing a high-frequency current sensor to directly capture the transmitting waveform. Through a peak detector with an adaptive threshold, the system accurately resolves the termination of transmitting current and triggers the acquisition of induced magnetic signal in the subsurface. Field experiments demonstrate that data acquired by the proposed receiver exhibits high consistency with the data collected by its own receiver in a commercial instrument, validating the effectiveness and practical value of this scheme in achieving cross-brand compatibility. This approach consequently overcomes the limitations that a transmitter can only be used together with its own receiver in TEM measurement, which is beneficial to interoperate between different systems and expand receiver channels in two or three-dimension scenarios.

Aeromagnetic unmanned helicopters generate more complex maneuvers during survey flights compared to the conventional manned and unmanned aerial vehicles, thus causing a stronger multicollinearity in the coefficient estimation for the magnetic interference compensation. This inevitably degrades both the precision and stability of aeromagnetic compensation. Because the existing aeromagnetic compensation methods can only degrade a single adverse effect, they are unsuitable for special unmanned helicopter-based aeromagnetic platforms. To address this issue, a novel method of balancing the compensation precision and stability is proposed in this paper. A regularization term incorporating a dynamic weight matrix is first introduced to constrain the feasible solution space of interference compensation coefficients, thus improving the compensation precision. For ensuring the stability of aeromagnetic compensation, a parameter optimization method for the regularization term based on the cross validation-gray wolf optimizer is also proposed to adaptively determine the optimal parameters. A dedicated unmanned helicopter-based aeromagnetic platform and a compensator were built to validate the above method. The results from two flight experiments demonstrate improvement ratios of 14.3 and 9.3 for the proposed method, corresponding to 2.0 and 3.0 times higher than those of the state-of-the-art commercial compensator, and 6.2 and 2.0 times higher than those of the Principal Component Analysis(PCA), enabling superior compensation precision. Additionally, the fluctuation in standard deviations is only 16.7% of that of the commercial compensator, and only 9.1% of that of the PCA confirming enhanced compensation stability.

The fluxgate sensor is the most widely used sensor in vector magnetic measurement. However, during long-term continuous observation, the fluxgate sensor will produce large measurement errors due to changes in ambient temperature. This paper proposes a temperature calibration method for the fluxgate sensor based on polynomial fitting to address the temperature error of fluxgate sensors. First, the effect of temperature on the performance indicators of the fluxgate sensor was analyzed. Second, according to the existing temperature-magnetic field data, a temperature calibration model of the fluxgate sensor was constructed. Compared with other temperature calibration methods, the result shows that the proposed temperature calibration method is relatively simple and can better achieve real-time calibration for sensor application scenarios. Finally, to verify the effectiveness of the proposed method, numerous laboratory experiments were implemented. The temperature drift was reduced from about 700 nT before calibration to about 1 nT, root mean square error RMSE = 11.7189, indicating that the proposed method has a good temperature calibration effect on the data measured by the fluxgate sensor within the variable temperature background.

The three-axis fluxgate sensor is the most widely used sensor in vector magnetic measurement. This paper proposes a calibration method for the cumulative error of the three-axis fluxgate sensor considering the influence of temperature. Firstly, various errors of the three-axis fluxgate sensor were analyzed and the cumulative error model was established. The parameters of the sensor cumulative error model were calculated based on the Particle Swarm Optimization-Genetic Algorithm (PSO-GA) optimization algorithm. Then, the water bath heating method was used to implement scalar comparison experiments between the three-axis fluxgate sensor and a reference Overhauser magnetometer at different temperatures. Experimental results show that temperature affects the scale factor coefficients in the error calibration parameters of the three-axis fluxgate sensor, and the scale factor coefficients q_x , q_y , q_z of the three axes have similar trends with temperature. Finally, we designed validation experiments for the proposed calibration method. During long-term magnetic field measurement, using the fixed scale factor coefficient matrix Q for calibration still has a large deviation from the trend of the reference field, with the maximum deviation being about 150 nT. However, using the scale factor coefficient matrix Q( T ) that changes with temperature for calibration, the trend of the calibrated magnetic field is basically consistent with the reference field, and the maximum deviation is less than 20 nT. This means that the proposed method has a better calibration effect.

Multifunctional magnetometers enable high-precision observations of the geomagnetic direction and total magnetic field, which have broad applications in geoscience research and space weather forecasting. However, inconsistencies still occur between the optical and magnetic axes of classic multifunctional magnetometers, and few studies have investigated their direct detection. To address this issue, we propose a novel method for the detection of the optical-magnetic axis inconsistency. The magnetic azimuths for the magnetic axis and the optical axis of the multifunctional magnetometer are determined through the bias field loading and fluxgate theodolite, thereby allowing direct detection of the inconsistency. The proposed method is also modeled to quantify the detection errors introduced by the total-field sensor and the observation operation. In addition, we develop a dedicated experimental platform and conduct comparative tests at a geomagnetic observatory to validate the practicality and performance of the method. The experimental results show that the proposed method can significantly reduce the deviation of the declination curve measured by the multifunctional magnetometer relative to the curve measured by the fluxgate theodolite from 3959′′ to 19′′, achieving a 99.5% reduction rate.