Bow-tie antennas are utilized extensively in ground-penetrating radar (GPR) systems. In order to achieve sufficient penetration depth and resolution, the bow-tie antennas for GPR applications require low operating frequency, high gain, and excellent broadband. A novel ultra-wideband (UWB) bow-tie antenna with gain enhancement for GPR applications is proposed in this paper. First, a UWB bow-tie antenna with resistive loading is designed. The metal reflector and metamaterial loading make the bow-tie antenna directional, and loading the same metamaterial on the front side of the antenna further improves directional gain. After testing, the lowest frequency of the fabricated antenna is 317 MHz, the relative bandwidth is 98.6%, the peak gain in the frequency range is 9.3 dBi, and the size is only 0.38 λ at the lowest frequency. The proposed compact antenna takes both gain and bandwidth into consideration. Finally, in order to further verify the effectiveness of the proposed antenna in the GPR system, a stepped frequency continuous wave ground-penetrating radar (SFCW-GPR) system was built. The experimental results show that the designed antenna is suitable for the GPR system of deep penetration and high-resolution detection, which is beneficial to the imaging of underground structures.

The Gaussian pulse generator is the core component of the pulse ground penetrating radar (GPR) system, which requires high amplitude, narrow pulse width, and low ringing levels. Marx circuits are widely used to generate Gaussian pulses. However, due to the complex pulse-forming process, the high-amplitude pulses generated by conventional Marx circuits suffer from oscillation and severe ringing. In this article, a refined model of the Marx circuit based on lossy transmission line theory is proposed, which effectively reduces the oscillation and ringing level of the generated Gaussian pulses. Furthermore, a monocycle pulse-shaping network is proposed based on the short-circuit stub. The unipolar Gaussian pulse is converted into a Gaussian monocycle pulse for antenna radiation. Waveform experiment results show that the peak-to-peak value of the output pulse is 428 V, the pulse width is about 0.8 ns, and the ringing level is low at about 9%. The profile imaging result of the sand tank detection experiment further shows that the generated high-quality Gaussian monocycle pulse can provide good detection performance of underground buried targets for the pulse GPR system.

Random noise greatly affects the quality of transient electromagnetic (TEM) signals in urban environments, leading to reduced detection accuracy. The effectiveness of denoising methods such as filtering or modal decomposition is limited by manually selecting parameters, and some noises are bound to be retained. In this letter, a novel approach combining reptile search algorithm (RSA) optimized variational mode decomposition (VMD) with deep neural network (DNN) is proposed to identify and eliminate noise. First, RSA is used to select key parameters in VMD. Then, based on the optimized parameters, the noisy signal is decomposed into different intrinsic mode functions (IMFs) via VMD, and the cross-correlation (CC) coefficient is used to select and reconstruct the effective signal. To solve the problem of residual noise, the convolutional neural network (CNN) and long short-term memory are combined to extract the time-related features of the data and further improve the signal-to-noise ratio (SNR). RSA-VMD-DNN is a denoising method that is better suited for random noise in nonlinear and nonstationary TEM signals. It can effectively select and reconstruct signals while eliminating residual noise. The results show its great potential for improving the accuracy and reliability of TEM detection.

The small-loop transient electromagnetic (TEM) method can effectively investigate urban underground space. However, due to the severe mutual induction between the transmitting and receiving coils, the secondary field signal containing underground shallow information is contaminated by the primary field interference. Weak-coupling coils can reduce the effect of mutual induction, but the residual mutual induction (RMI) still affects the early secondary field response, resulting in the loss of shallow information. In this article, we take the bucking coil as a case to refine the model of the small-loop TEM weak-coupling coil and propose an RMI uncertainty quantification method based on sparse polynomial chaos expansion to guide the coil design. The simulation results show that compared with the conventional design method, considering the refined structure of the wire layer overlap can more effectively reduce RMI in the presence of processing and installation errors. The experimental results show that the new structure proposed can improve the ability to distinguish the anomalous body in the shallow space of the urban underground space and has strong practicality.

Aiming at the problem that the leakage magnetic field (LMF) generated by wireless power transfer (WPT), a surrounding active shielding coil structure, and its fast multiobjective optimization design method is proposed. First, considering the problem that active shielding can reduce the efficiency of WPT, a surrounding active shielding coil structure that is inversely connected in series to the WPT coil is proposed, and the inner shielding coil compensates for the efficiency. Then, taking the efficiency of the WPT and the maximum magnetic flux density of the measurement surface as the optimization objectives, combining the data-driven polynomial chaos metamodel method and the optimization method based on the non-dominated sorting genetic algorithm, a fast multiobjective optimization design of the surrounding active shielding coil structure is achieved. Finally, an experiment was conducted using a 300 W WPT. At fixed observation point, the surrounding active shielding coil structure proposed in this article reduced the LMF by 86.97%, and the induced electric field strength of the human body exposed to the LMF was reduced by 65.40%, while the efficiency of the WPT was only reduced by 0.28%, proving the surrounding active shielding coil and its efficient design method are effective.

Electromagnetic compatibility (EMC) of electrical equipment is frequently affected by a lot of aleatory and epistemic uncertainties, which may result in a serious decline in the EMC of equipment. Accordingly, the mixed epistemic–aleatory uncertainty quantification (UQ) is crucial in the performance assessment and optimization of EMC. This study proposes a mixed UQ and imprecise sensitivity analysis (ISA) method based on probability box (p-box) theory and polynomial chaos (PC). The method treats the epistemic uncertainty of the parameters in the p-box as a quadratic polynomial function of the PC coefficients, thereby quantifying the mixed uncertainty by calculating the p-box of the response. We also further combine the PC-pbox and Sobol sensitivity analysis methods to conduct ISA on each input variable, quantifying and separating the effect of aleatory and epistemic uncertainties on EMC. Finally, taking the problem of the transmission line crosstalk as an example, this study quantifies the mixed uncertainty and ISA of the induced current. The results show that the proposed method can efficiently and accurately realize the mixed UQ and ISA of the EMC evaluation and provide a theoretical basis for EMC assessment and optimization.