Since the height of sea detection radar antenna and ship targets is relatively low, it is generally believed that its over-the-horizon detection is mainly caused by the evaporation duct at sea. To fully understand the influence of atmospheric ducts on radar over-the-horizon detection, a shore-based navigation radar was used to carry out over-the-horizon detection experiments; radiosondes were used to measure the atmospheric profile and evaporation duct monitoring equipment was used to measure the evaporation duct. Based on experimental data and model simulation, a comparative analysis of a navigation radar’s over-the-horizon detection, the evaporation duct, and the lower atmospheric duct is presented in this study. The results show that the atmospheric duct can affect the signal propagation of the navigation radar, thus resulting in over-the-horizon detection. The long-range over-the-horizon detection of the navigation radar is caused by the strong lower atmospheric duct, while the evaporation duct can generally only form weak over-the-horizon detection, which is different from the general cognition.

Using intelligent optimization algorithms to retrieve atmospheric duct parameters by monitoring automatic identification system (AIS) signals at sea is a new passive remote sensing technology for atmospheric ducts. To thoroughly compare and analyze the inversion results of different intelligent optimization algorithms and optimize the parameters of the algorithms, this study considered a simulated atmospheric duct environment for atmospheric duct inversion using the genetic, simulated annealing, and particle swarm optimization (PSO) algorithms. The results indicated that the PSO algorithm exhibited the best inversion performance. The inversion results of the simulated annealing particle swarm optimization (SAPSO) and PSO algorithms under different inversion parameters were further statistically analyzed, and the atmospheric duct parameters were obtained from measured AIS signals based on the SAPSO algorithm. The inversion results verified the effectiveness of the proposed algorithm, and they continuously improved with additional calculations in the inversion algorithm. However, the changing trend gradually slowed. Therefore, in practical applications, the inversion time consumption should be balanced with the inversion effect to optimize the inversion parameters.

In this paper, a multi-frequency MIMO antenna for 5G and Wi-Fi 6E is presented. The antenna uses a cosine-shape monopole and split-ring resonator (SRR) structure for tri-band radiation, and frequency band expansion is achieved through SRR, folded split-ring resonators (FSRR) and Archimedean spiral metasurfaces for decoupling, with which a combination of surface wave and space wave decoupling is achieved. The Archimedean spiral metasurface unit can achieve space wave decoupling in the tri-band. By adopting the method of combining space wave decoupling and surface wave decoupling, the miniature antenna is achieved. The measured results closely align with the simulated results. Specifically, maintaining a reflection coefficient of −10 dB, the measured results indicate an increase in isolation of 3.5 dB, 36.47 dB, and 6.42 dB for the frequency bands of 3.45–3.55 GHz, 5.7–5.9 GHz, and 6.75–7 GHz, respectively. Additionally, the MIMO antenna demonstrates an average efficiency of approximately 89%, with an average envelope correlation coefficient (ECC) of 0.0025. Furthermore, the antenna’s peak gain increases by 4.3 dB at 3.5 GHz, 3.8 dB at 5.8 GHz, and 1.9 dB at 6.9 GHz upon integrating the metasurface. The proposed method and structure are anticipated to contribute significantly to decoupling in multi-frequency MIMO antennas.

Parabolic equations (PE) are commonly employed for calculating the spatial propagation loss of wireless signals. The initial field is a crucial factor. To investigate the impact of construction accuracy on the calculation of radio wave propagation loss, we selected the half-wave dipole antenna and its Gaussian approximation to examine the influence of wide-angle PE modeling. We analyzed the disparities between the actual antenna pattern and the Gaussian beam approximation, as well as the discrepancies in the corresponding initial field and the calculation of radio wave propagation loss in PE modeling. The simulation results indicate that the error of the Gaussian approximation increases as the angle of departure from the antenna main beam increases, with a relative error of approximately 30% in the initial field. A comparison between the experimental test of the broadcast signal and the simulation calculation reveals that the model based on the actual antenna aligns more closely with the measured value on a flat underlying surface. However, in mountainous areas with significant fluctuations, the simulation results are consistent with each other and higher than the measured value. The inversion results obtained through the particle swarm optimization algorithm demonstrate that the model based on the actual antenna exhibits superior inversion accuracy for the tropospheric atmospheric duct structure.

A novel frequency-selective polarization converter (FSPC) is proposed based on the new method of combining a polarization conversion metasurface (PCM) with a bandpass frequency-selective surface (FSS), which provides an efficient transmission band and broadband radar cross-section (RCS) reduction. The upper and lower layers are combined to form the proposed FSPC. In the upper layer design, the bowtie-shaped structure is used to achieve polarization conversion on both sides of the transmission band. Regarding the lower layer design, the second-order bandpass FSS is employed, which acts as an equivalent ground for the polarization conversion layer outside the passband and provides a highly efficient transmission window within the passband. Ultimately, the magnitude of the co-polarized reflection of the FSPC that is below −10 dB ranges from 5.1 GHz to 16.1 GHz, with a relative bandwidth of 104%, and the co-polarized transmission window with an insertion loss of less than 1 dB is presented ranging from 8.7 GHz to 12.6 GHz, with a relative bandwidth of 36%. Furthermore, by arranging the upper bowtie-shaped PCM in a checkerboard pattern, the monostatic RCS can be effectively reduced in a broad frequency range. Samples of the proposed design are fabricated for the measurement verification of performance. The results show that the measurement results match well with the simulation results. Compared with other designs, the proposed FSPC exhibits efficient co-polarized transmission, with insertion loss as low as 0.34 dB and the passband flatness being good.

This article investigates how to exploit the high-frequency mmWave for 5G-advanced and beyond, which requires new filters for the wide bandpass and its multi-sub-band. Based on the substrate-integrated waveguide (SIW), spoof surface plasmon polariton (SSPP), and metastructures, like complementary split-ring resonators (CSRRs), the development of a wide bandpass filter and a multi-sub-band filter is proposed, along with an experimental realization to verify the model. The upper and lower cutoff frequencies of the wide bandpass are controlled through an SIW-SSPP structure, whereas the corresponding wide bandpass and its multi-sub-band filters are designed through incorporating new metastructures. The frequency range of 24.25–29.5 GHz, which covers the n257, n258, and n261 bands for 5G applications, was selected for verification. The basic SIW-SSPP wide bandpass structure of 24.25–29.5 GHz was designed first. Then, by incorporating an Archimedean spiral configuration, the insertion loss within the passband was reduced from 1 dB to 0.5 dB, while the insertion loss in the high-frequency stopband was enhanced from 40 dB to 70 dB. Finally, CSRRs were integrated to effectively suppress undesired frequency components within the bandpass, thereby achieving multi-sub-band filters with low insertion losses with a triple-sub-band filter of 0.5 dB, 0.7 dB, and 0.8 dB in turn. The experimental results showed strong agreement with the design scheme, thereby confirming the rationality of the design.