Among the inversion methods for airborne transient electromagnetic data, the hybrid inversion method integrates the iterative optimization framework with artificial neural networks (ANNs), ensuring inversion accuracy while enhancing the generalization capability of neural networks. However, this method faces challenges in terms of slow computation speeds due to its lower update step-length and the lack of consideration for electromagnetic response laws. Our method adopts supervised descent method (SDM) framework to supervise the artificial neural networks, obtaining a longer update step-length. On the basis of the SDM framework, we have considered the electromagnetic response laws and designed RNN-ResNet and 1D-Unet networks to update conductivity model, improving the computing speed. Through numerical ablation experiments, we validated the effectiveness of our proposed method and compared the inversion results with those obtained using the traditional hybrid method. Additionally, we conducted tests on bundle fringe distribution, inversion fitting loss, noise sensitivity, and inversion speed for both methods using measured data to evaluate their performance in practical applications. The experimental findings demonstrate that our method achieves the same level of inversion accuracy and generalization ability as the traditional hybrid method while enhancing inversion speed by up to 68.5%.

The group velocity of lightning electromagnetic signals plays an important role in lightning location systems using the time difference of arrival (TDOA) method. Accurate estimation of group velocity is difficult due to the space- and time-varying properties of the Earth-ionosphere waveguide. Besides, the analytical solution of the group velocity is difficult to obtain from the classic mode theory, especially when higher-order modes, anisotropic geomagnetic background, diffuse ionosphere profile, and propagation path segmentation are all taken into consideration. To overcome these challenges, a novel numerical method is proposed in this paper to estimate the group velocity of the lightning signal during ionospheric quiet periods. The well-known Long Wavelength Propagation Capability (LWPC) code is used to model the propagation of VLF/LF radio waves. Since LWPC uses a simplified ionospheric model which is unable to describe the subtle variations of ionospheric parameters over time and space, the IRI-2016 model is incorporated into the numerical modeling process to provide more accurate ionosphere parameters. Experimental results of a VLF/LF lightning location network are demonstrated and analyzed to show the effectiveness of our method. The proposed method is also applicable when there is a sudden ionospheric disturbance as long as the parameters of the ionosphere are obtained in real time by remote sensing methods.

Cesium optically pumped magnetometers are widely used in geophysical exploration, environmental monitoring, and scientific research for magnetic field measurements. Traditional magnetometer systems, however, encounter limitations in complex environments due to magnetic interference, low data acquisition efficiency, and inadequate real-time control, which affect both application and accuracy. To overcome these challenges, this paper presents a software system designed for cesium optically pumped magnetometers. The system incorporates automatic probe switching, data acquisition, user interface control, and a compensation algorithm. The automatic switching function mitigates dead zones in the optically pumped probes, ensuring continuous data collection. The data acquisition module supports multiple formats and transmission protocols, enhancing efficiency and ensuring data integrity. The user interface facilitates real-time monitoring and control of magnetometer operations. The system employs the Tolles–Lawson model to effectively suppress environmental magnetic interference, ensuring high-precision measurements even in complex environments. Experimental results confirm the system's enhanced sensitivity and stability, making it a reliable tool for precise magnetic field measurements in challenging conditions.

In order to meet the challenges of transient electromagnetic exploration in complex terrain, a lightweight, low-noise, three-component, fully-airborne transient electromagnetic system is designed based on an unmanned aerial vehicle platform. By receiving the three-component electromagnetic field, reliable detection of the normal component even in undulating terrain is enabled, while also offering a theoretical basis for correcting errors arising from receiver coil oscillation. Through a system-level optimization design, the system balances weight and transmission power, resulting in a lightweight (14.94 kg), large transmitting magnetic moment (2250 Am²), and extremely low system noise (1.7 nT/s) configuration. A series of performance verification experiments and field tests verify the stability and practical operability of the proposed system in field applications. Comparisons between the inversion results of the collected detection data and borehole logging data further confirm the reliability of the system. Therefore, this system can provide an effective technical approach and solid data support for the fine detection of subsurface interfaces within a depth of 50 meters.

In order to meet the challenges of transient electromagnetic exploration in complex terrain, a lightweight, low-noise, three-component, fully-airborne transient electromagnetic system is designed based on an unmanned aerial vehicle platform. By receiving the three-component electromagnetic field, reliable detection of the normal component even in undulating terrain is enabled, while also offering a theoretical basis for correcting errors arising from receiver coil oscillation. Through a system-level optimization design, the system balances weight and transmission power, resulting in a lightweight (14.94 kg), large transmitting magnetic moment (2250 Am²), and extremely low system noise (1.7 nT/s) configuration. A series of performance verification experiments and field tests verify the stability and practical operability of the proposed system in field applications. Comparisons between the inversion results of the collected detection data and borehole logging data further confirm the reliability of the system. Therefore, this system can provide an effective technical approach and solid data support for the fine detection of subsurface interfaces within a depth of 50 meters.

In order to meet the challenges of transient electromagnetic exploration in complex terrain, a lightweight, low-noise, three-component, fully-airborne transient electromagnetic system is designed based on an unmanned aerial vehicle platform. By receiving the three-component electromagnetic field, reliable detection of the normal component even in undulating terrain is enabled, while also offering a theoretical basis for correcting errors arising from receiver coil oscillation. Through a system-level optimization design, the system balances weight and transmission power, resulting in a lightweight (14.94 kg), large transmitting magnetic moment (2250 Am²), and extremely low system noise (1.7 nT/s) configuration. A series of performance verification experiments and field tests verify the stability and practical operability of the proposed system in field applications. Comparisons between the inversion results of the collected detection data and borehole logging data further confirm the reliability of the system. Therefore, this system can provide an effective technical approach and solid data support for the fine detection of subsurface interfaces within a depth of 50 meters.