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Traditional ground-penetrating radar (GPR) data inversion leverages iterative algorithms that suffer from high computation costs and low accuracy when applied to complex subsurface scenarios. Existing deep learning-based methods focus on the ideal homogeneous subsurface environments and ignore the interference due to clutters and noise in real-world heterogeneous environments. To address these issues, a two-stage deep neural network (DNN), called DMRF-UNet, is proposed to reconstruct the permittivity distributions of subsurface objects from GPR B-scans under heterogeneous soil conditions. In the first stage, a U-shape DNN with first multi-receptive-field convolution (MRF-UNet1) is built to remove the clutters due to inhomogeneity of the heterogeneous soil. Then, the denoised B-scan from MRF-UNet1 is combined with the noisy B-scan to be inputted to the DNN in the second multi-receptive-field convolution (MRF-UNet2). MRF-UNet2 learns the inverse mapping relationship and reconstructs the permittivity distribution of subsurface objects. To avoid information loss, an end-to-end training method combining the loss functions of two stages is introduced. A wide range of subsurface heterogeneous scenarios and B-scans are generated to evaluate the inversion performance. The test results in the numerical experiment and the real measurement show that the proposed network reconstructs the permittivities, shapes, sizes, and locations of subsurface objects with high accuracy. The comparison with existing methods demonstrates the superiority of the proposed methodology for the inversion under heterogeneous soil conditions. [ABSTRACT FROM AUTHOR]

In this paper, the precipitable water vapor (PWV) data from Global Navigation Satellite System (GNSS) is introduced into ITU-R cloud attenuation model for higher temporal and spatial resolution for a tropical region. The revised model incorporates PWV value for estimation of cloud integrated liquid water content (ILWC) and then determines the cloud attenuation. In this study, ILWC along the propagation path is obtained by processing radiosonde vertical profile using the combination of a water vapor pressure cloud detection model and the Salonen and Uppala liquid water density model. From the analysis of 2 years of radiosonde data from eight sites within the tropical region, the results show that the ILWC along the path can be approximated by a power function relationship with the PWV. The estimated cloud attenuation using the improved model is compared with the values calculated using the ITU-R model and the cloud attenuation derived from a Ka-band beacon data. The results show that the proposed model is in good agreement with the ITU-R model at high percentage of time exceedance for the thin layer of stratus clouds and matches well with cloud attenuation suffered from beacon signal at low percentage of time exceedance for the thick layer of cumulonimbus clouds. [ABSTRACT FROM AUTHOR]

An effective technique is proposed to extend the impedance bandwidth of a near-ground antenna without significantly degrading the realized gain in this communication. This is achieved by coating the ground plane under the antenna with ferrite tiles. Since the current density is found to indicate the magnetic field and image current density on the ground, ferrite tiles are used to coat the ground plane in regions where there is a high current density concentration. In addition, the end loading is also implemented to extend the bandwidth of the antenna at the lower frequency bound. An HF low-profile antenna is used to verify the proposed method. The height of this antenna can be reduced to $0.023\lambda $ using the ferrite tiles, and the lower bound of the bandwidth can be reduced from 7 to 2 MHz. The HF broadband antenna is fabricated, and the measurement is performed to verify the simulated results. [ABSTRACT FROM PUBLISHER]

This paper proposes a model for predicting rain attenuation in the tropical region. Slant path rain attenuation measurements were carried out in Singapore by analyzing the beacon signals from two satellites, namely WINDS and GE23, operating at frequencies of 18.9 and 12.75 GHz, respectively. Rainfall rates at the location of the beacon receivers were recorded. The cumulative distributions of the rainfall rate and the corresponding rain attenuation are presented and analyzed. It is found that the cumulative distribution of the measured rainfall rate is close to that predicted by the ITU-R model. Measurement data from a total of nine countries are compared with four existing rain attenuation prediction models, namely the Yamada, DAH, Karasawa, and Ramachandran models. Results show that although three of these models have relatively good prediction capability for the tropical region, they could be improved. Therefore, in this paper, a slant path rain attenuation model suitable for the tropical region is proposed. This is done by using the complementary cumulative distributions of rain attenuation for satellite links measured in Singapore and five other tropical countries. The proposed model is found to outperform existing models. [ABSTRACT FROM PUBLISHER]

A comparative analysis of the rain attenuation evaluated from beacon measurements and from a single polarization S-band Radar is performed. The beacon measurements are obtained for two slant satellite paths with different elevation angles in the Ku- and Ka-band. The single polarization S-band Radar reflectivity data is used to predict the attenuation along the satellite propagation paths. This is done by first converting the reflectivity into rain rate using the Z-R relations suitable for the tropical region and, afterwards, by evaluating the slant path attenuation through the integration of the specific rain attenuation derived from the point rainfall rate. An empirical calibration factor for the Radar reflectivity is provided. A comparison of the rain fade suffered from the two satellite paths is presented both on event basis and in terms of cumulative distribution functions. The empirical calibration factor and a single Z-R relation suitable for the tropical region are used for rain attenuation evaluation from single polarization Radar data. [ABSTRACT FROM PUBLISHER]

Site diversity is an effective rain attenuation mitigation technique, especially in the tropical region with high rainfall rate. The impact of different factors such as site separation distance, frequency, elevation angle, polarization angle, baseline orientation and wind direction is assessed. Results are compared to those reported in existing literature and also compared to the commonly used ITU-R site diversity prediction models. The effect of the wind direction on site diversity is also presented. It can be observed that diversity gain is highly dependent on the site separation distance, elevation angle and wind direction but independent of the frequency, baseline angle and polarization angle of the signal. This study is useful for the implementation of site diversity as a rain attenuation mitigation technique. [ABSTRACT FROM AUTHOR]

Near ground radio wave propagation is examined in a tropical plantation experimentally at VHF and UHF bands. The propagation loss with forest depth is empirically analyzed using an integrated model combining both the foliage induced effect and the ground effect. Several well-known empirical foliage models are compared and analyzed. It is observed that the fitted ITU-R model taking into account the ground reflection, can provide a close approximation to the path loss in a tropical palm plantation. However, the accuracy of this model becomes poor when lateral wave dominates in the VHF band. A modification to the ITU-R model is then proposed taking into consideration the lateral wave effect. The modified model is verified using measured and found to have higher accuracy for large foliage depth in the VHF band as compared to the existing empirical foliage models. [ABSTRACT FROM AUTHOR]