Tao Wu

Electromagnetic vortex waves have received widespread attention in many fields due to their unique physical characteristics. The information dimension provided by vortex electromagnetic waves brings possibilities for future breakthroughs in radar detection and imaging. This article proposes a multi-modal aggregated electromagnetic vortex wave generation method for the first time. Moreover, it conducts vehicle imaging experiments to verify the method’s practicality. The core element of the experiment is to simultaneously generate multiple-mode electromagnetic vortex wave signals with energy accumulation and perform fusion processing. Firstly, multiple orbital angular momentum (OAM) modes are superimposed to generate a mode group, and the initial phase of the modes in the mode group is further controlled to synthesize aggregated electromagnetic vortex waves. Based on the generation of aggregated vortex waves, imaging experiments were conducted using a vehicle-mounted setup. The experimental procedure and multi-modal fusion results were presented. It has been shown that the energy of the main lobe signal of the image target is enhanced by utilizing multi-modal vortex radar information fusion, which can improve the signal-to-noise ratio of the target imaging.

A modified physical optics (PO) scattering algorithm for analyzing the high-frequency electromagnetic (EM) scattering of vortex wave fields is proposed in this Letter. While traditional PO methods struggle to accurately model edge diffraction effects in orbital angular momentum (OAM)-carrying beams, especially for complex targets, we address this limitation by integrating the equivalent edge current (EEC) theory into the conventional PO framework. By decomposing the Bessel vortex wave into a spectrum of plane wave components, we independently compute the PO and EEC scattering contributions for each spectral element. The coherent superposition of these contributions yields the total scattered field, significantly improving modeling accuracy. Numerical results demonstrate a 20%–30% enhancement in radar cross section prediction accuracy over the standard PO method. The proposed hybrid PO and EEC algorithm offers a computationally efficient solution for vortex EM scattering analysis, with direct applications in OAM-based radar systems, computational imaging, and next-generation communications.

This communication proposes a 2-bit dual-linear polarized reconfigurable transmitarray (DLPRTA) operating at Ku-band. The independent dual-linear polarization unit cell consists of two mutually orthogonal subunit cells with identical structures. The subunit cell is a receiver-transmitter structure, which is composed of an active symmetrical receiving dipole and an active asymmetric transmitting dipole respectively integrated with a pair of p-i-n diodes. A total of four p-i-n diodes of each subunit cell realize four operating states of the 2-bit phase quantization. A DLPRTA prototype consisting of 22×22 unit cells was designed, fabricated, and measured. At 15.2 GHz, the maximum gains of the DLPRTA in x- and y-polarization are 24.65 dBi and 24.61 dBi, respectively, corresponding to the aperture efficiency of 23.85% and 23.59%. Its beam scanning capability has also been verified to cover the scan range of ±50° in both linear polarizations with side-lobe levels lower than 10 dB. The gain loss of the maximum angle beam scanning are 2.26 dB and 2.37 dB respectively, which proved good beam scanning performance.

In this paper, we present a metal-only transmission metasurface adopting dual-layer elements with I-shaped grooves etched on each layer, which is designed for orbital angular momentum (OAM) generation. The special arrangement of the grooves on the elements results in a wider phase compensation range, and by varying the length of the grooves, a full 360° phase coverage with a transmission amplitude of more than −2 dB can be achieved at 10 GHz. As a proof of concept, a metal-only transmission metasurface composed of 400 elements is designed, fabricated, and measured. The simulated and measured results suggest that the OAM transmitted waves with the mode l = −1 can be efficiently generated by a double-layer metal-only metasurface at around 10 GHz. Compared with conventional configurations of OAM transmitted beam generation, this configuration has great potential for high power microwave and space environment applications.

Accurate modeling of sea clutter amplitude distribution plays a crucial role in enhancing the performance of marine radar. Due to variations in radar system parameters and oceanic environmental factors, sea clutter amplitude distribution exhibits multiple distribution types. Focusing solely on a single type of amplitude prediction lacks the necessary flexibility in practical applications. Therefore, based on the measured X-band radar sea clutter data from Yantai, China in 2022, this paper proposes a multi-task one-dimensional convolutional neural network (MT1DCNN) and designs a dedicated input feature set for the joint prediction of the type and parameters of sea clutter amplitude distribution. The results indicate that the MT1DCNN model achieves an F1 score of 97.4% for classifying sea clutter amplitude distribution types under HH polarization and a root-mean-square error (RMSE) of 0.746 for amplitude distribution parameter prediction. Under VV polarization, the F1 score is 96.74% and the RMSE is 1.071. By learning the associations between sea clutter amplitude distribution types and parameters, the model’s predictions become more accurate and reliable, providing significant technical support for maritime target detection.

A novel metal-only transmitarray (TA) operating in linear polarization in the $X$ -band for beam scanning is proposed in this article. It is composed of metal-only unit cells with a double-layer structure, which obtains a complete 360 $^{\circ }$ phase shift range with low loss by adjusting the length of interleaved slots etched on the thin metal sheets. The feed displacement technique is used as a feasible mechanical control approach for beam scanning, and bifocal phase distribution is designed for the TA to improve the gain roll-off and the scanning coverage. In order to demonstrate the design scheme, a TA prototype consisting of 24 × 24 unit cells has been fabricated and measured. The measured results show that the proposed TA can achieve a maximum gain of 27.8 dBi at 10 GHz, and a scanning coverage from $-25^{\circ }$ to $+25^{\circ }$ with side-lobe level lower than 10 dB.

This paper presents a kind of metal-only anisotropic impedance holographic metasurfaces made up of periodic wavelength size-variable meta-atoms. The proposed meta-atom has only two metal layers, i.e. a upper patterned layer carved with cylindrical hollows connecting by a narrow metal cuboid, and a lower grounded layer. The two metal layers are separated by an air gap. The anisotropy of this tensor impedance meta-atom can be skillfully realized by simultaneously controlling the radius of cylindrical hollows and the orientation angle of the narrow metal cuboid. The relationship between the geometrical parameters of the meta-atoms arranged in different positions and the impedance strips with alternating light and shade can be directly mapped based on the integration of the holographic theory and the leaky-wave principle. For proof of concept, two metal-only anisotropic impedance holographic metasurfaces are applied to design linearly polarized broadside pencil beam and dual linearly polarized pencil beams with different radiation angles in the C-band. There is good consistency between the measurements and the simulated results. The satisfactory performance and ultralow profile metal-only structure with reduced fabrication complexity/cost make this proposed design a competitive candidate for space applications.

The high-precision prediction of sea clutter reflectivity is helpful in improving the performance of marine radar and sea surface remote sensing capabilities. Under the same sea state, when the significant wave height, wave period, wind speed, and other marine environmental parameters are different, the backward reflectivity of the sea clutter corresponding to the wave structure is not the same. Due to the complex and variable nature of sea clutter characteristics across various wave structures, a meticulous classification of wave structures by integrating multiple marine environmental parameters enables the achievement of the high-precision prediction of sea clutter reflectivity. In this study, utilizing measured data of diverse marine environmental parameters in the Yellow Sea, China, we applied the Affinity Propagation algorithm to data clustering. Based on the clustering outcomes, we accomplished a refined classification of wave structures and developed a discriminant model to precisely classify the refined wave structure, facilitating the categorization of new data. In order to achieve more accurate predictions of sea clutter reflectivity, this paper proposes a deep neural network model named GIT-HYB-DNN, which combines the empirical models GIT and HYB. The GIT-HYB-DNN model is applied to predict the reflectivity for each wave structure category separately. The results demonstrate that the root mean square errors of sea clutter reflectivity predictions for different wave structure categories in this study range from 0.62 dB to 0.84 dB. The prediction errors are significantly reduced compared to the root mean square error of 1.08 dB, which was obtained without refined wave structure classification. This study holds theoretical significance and practical value for the investigation of sea clutter characteristics and the selection of radar parameters.

The use of optical sensing for in vivo applications is compelling, since it offers the advantages of non-invasiveness, non-ionizing radiation, and real-time monitoring. However, the signal-to-noise ratio (SNR) of the optical signal deteriorates dramatically as the biological tissue increases. Although increasing laser power can improve the SNR, intense lasers can severely disturb biological processes and viability. Quantum sensing with bright squeezed light can make the measurement sensitivity break through the quantum noise limit under weak laser conditions. A bright squeezed light source is demonstrated to avoid the deterioration of SNR and biological damage, which integrates an external cavity frequency-doubled laser, a semi-monolithic standing cavity with periodically poled titanyl phosphate (PPKTP), and a balanced homodyne detector (BHD) assembled on a dedicated breadboard. With the rational design of the mechanical elements, the optical layout, and the feedback control equipment, a maximum non-classical noise reduction of −10.7 ± 0.2 dB is observed. The average squeeze of −10 ± 0.2 dB in continuous operation for 60 min is demonstrated. Finally, the intracavity loss of degenerate optical parametric amplifier (DOPA) and the initial bright squeezed light can be calculated to be 0.0021 and −15.5 ± 0.2 dB, respectively. Through the above experimental and theoretical analysis, the direction of improving bright squeeze level is pointed out.

At present, 5G base stations are densely distributed in major cities based on improving user concentrations and the large demand for services in urban hotspot areas. Moreover, 5G communication requires more accurate communication propagation loss (PL) monitoring. Low-build areas, such as suburbs and rural areas, are prone to forming relatively stable tropospheric ducts, which can bend the signal to the surface in the duct-trapping layer for multiple reflections. Due to the random flow of the atmospheric air mass, each reflection of the communication signal is re-scattered in the troposphere through the top of the duct layer, thereby expanding the propagation range of the signal and changing the expected effect of radio wave propagation. If ducting and troposcatter effects happen in the 5G base station antenna layer, co-channel interference (CCI) could occur, affecting the quality of electromagnetic propagation. Urban links in the plain area have no major terrain obstacles, but ground fluctuations and land cover scattering have a greater impact on the signal scattering at the bottom of the duct. On the basis of the forward-propagation theory, this paper adds factors, such as ducting the forecast value using real weather parameters, terrain, and land cover-type distributions to evaluate the CCIs of over-the-horizon communications on the intercity link. Based on 1300 sets of randomly generated terrains and landforms, two deep learning (DL) models were used to predict the PL of over-the-horizon communications between cities in a land-based ducting environment. The accuracy of LSTM prediction could reach 98.4%. The verification of PL prediction using DL in this paper allows for quick and efficient prediction of PL in the land-based ducting of intercity links using land cover characteristics.