Atmospheric Duct Detection Using Wind Profiler Radar and RASS

Hua, Wei; Shi-peng, SU; Tang, Haichuan; Jiao, Lin; Li, Yunbo

doi:10.1175/jtech-d-18-0009.1

Cited by 6 publications

(2 citation statements)

References 18 publications

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“…A method of detecting atmospheric ducts using a wind profiler radar and a radio acoustic sounding system was proposed in Ref. [ 20 ]. The measurements were carried out in the Liaoning Province of China.…”

Section: Related Work and Testbed Designmentioning

confidence: 99%

Remote Interference Discrimination Testbed Employing AI Ensemble Algorithms for 6G TDD Networks

Zhang

Zhou

et al. 2023

Sensors

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The Internet-of-Things (IoT) massive access is a significant scenario for sixth-generation (6G) communications. However, low-power IoT devices easily suffer from remote interference caused by the atmospheric duct under the 6G time-division duplex (TDD) mode. It causes distant downlink wireless signals to propagate beyond the designed protection distance and interfere with local uplink signals, leading to a large outage probability. In this paper, a remote interference discrimination testbed is originally proposed to detect interference, which supports the comparison of different types of algorithms on the testbed. Specifically, 5,520,000 TDD network-side data collected by real sensors are used to validate the interference discrimination capabilities of nine promising AI algorithms. Moreover, a consistent comparison of the testbed shows that the ensemble algorithm achieves an average accuracy of 12% higher than the single model algorithm.

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Section: Related Work and Testbed Designmentioning

confidence: 99%

Remote Interference Discrimination Testbed Employing AI Ensemble Algorithms for 6G TDD Networks

Zhang

Zhou

et al. 2023

Sensors

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“…As the research going, numerous methods have been developed. The most basic approach to obtaining atmospheric refractivity is to directly measure the meteorological elements using meteorological sounding equipment [8]. However, the temporal and spatial resolution is restricted by the measuring devices, which are costly and complicated to operate.…”

Section: Introductionmentioning

confidence: 99%

Inversion for Inhomogeneous Surface Duct without a Base Layer Based on Ocean-Scattered Low-Elevation BDS Signals

Liu

Cao

et al. 2021

Remote Sensing

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The anomalous propagation conditions, particularly the tropospheric ducts, severely impact the regular operation and performance evaluation of radio devices in the atmospheric boundary layer. Therefore, it is necessary to provide the regional distribution of tropospheric ducts for utilizing or avoiding these abnormal propagation phenomena. As significant uncooperative signal sources, the global navigation satellite systems (GNSS) have been widely applied in the remote sensing of the ocean and atmosphere due to the greater convenience and lower cost. With the completed deployment of the BeiDou Navigation Satellite System (BDS) in 2020, an additional source can be chosen in the relevant studies. Taking the BDS as an example, since the scattered signals from the ocean surface at low satellite elevation angles can be effectively trapped by tropospheric ducts, we propose a method to invert for the regional distribution of tropospheric ducts using the received power of ocean-scattered signals in this paper. Firstly, the propagation model was built to calculate the received power, and a suite of simulations was made in various atmospheric environments. The results suggested that the received power is more sensitive to the surface duct without a base layer. Then, we made a preliminary estimation of the tropospheric ducts on the ocean nearby Qingdao utilizing the Weather Research and Forecasting (WRF) model as well as the echo data measured by a Doppler weather radar. Before the inversion, the actual satellite azimuth and elevation angles should be obtained to evaluate the bistatic scattering coefficients and the received powers of the selected satellite signals. Finally, we presented an inversion example using the proposed method. In absence of the actual measurements, the received powers pre-estimated at different SNRs served as the inputs of the inversion process and the estimated duct parameters were used to verify the validity of the proposed inversion method. For both the received power and modified refractivity profile, the fitness between the values pre-estimated using the estimated duct parameters and calculated by the inverted duct parameters gets better as the elevation angle decreases and the SNR increases. The variation of the fitness between the estimated and inverted values is slightly different for each duct parameter. Moreover, the calculation of inversion errors further explained the above behaviors, including the mean absolute error (MAE) and the root mean square error (RMSE). Despite some certain errors, the inversion results maintain the overall tendencies and most characteristics of the estimated values, thus proving the validity of the inversion method.

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Trends and frontiers of atmospheric duct research based on CiteSpace and deep learning

Wei

Zhang³

et al. 2022

Environ Sci Pollut Res

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Atmospheric Duct Detection Using Wind Profiler Radar and RASS

Cited by 6 publications

References 18 publications

Remote Interference Discrimination Testbed Employing AI Ensemble Algorithms for 6G TDD Networks

Remote Interference Discrimination Testbed Employing AI Ensemble Algorithms for 6G TDD Networks

Inversion for Inhomogeneous Surface Duct without a Base Layer Based on Ocean-Scattered Low-Elevation BDS Signals

Trends and frontiers of atmospheric duct research based on CiteSpace and deep learning

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