Search Results (48)

THz communication stands as a pivotal technology for 6G networks, designed to address the critical challenge of data demands surpassing current microwave and millimeter-wave (mmWave) capabilities. However, realizing Tbps and kilometer-range transmission confronts the “dual attenuation dilemma” comprising severe free-space path loss (FSPL) (>120 dB/km) and atmospheric absorption. This review comprehensively summarizes our group′s advancements in overcoming fundamental challenges of long-distance THz communication. Through systematic photonic–electronic co-optimization, we report key enabling technologies including photonically assisted THz signal generation, polarization-multiplexed multiple-input multiple-output (MIMO) systems with maximal ratio combining (MRC), high-gain antenna–lens configurations, and InP amplifier systems for complex weather resilience. Critical experimental milestones encompass record-breaking 1.0488 Tbps throughput using probabilistically shaped 64QAM (PS-64QAM) in the 330–500 GHz band; 30.2 km D-band transmission (18 Gbps with 543.6 Gbps·km capacity–distance product); a 3 km fog-penetrating link at 312 GHz; and high-sensitivity SIMO-validated 100 Gbps satellite-terrestrial communication beyond 36,000 km. These findings demonstrate THz communication′s viability for 6G networks requiring extreme-capacity backhaul and ultra-long-haul connectivity. Full article

Passive Microwave Imagers (PMWIs) aboard meteorological satellites have been instrumental in advancing the understanding of Earth’s atmospheric and surface processes, providing invaluable data for weather forecasting, climate monitoring, and environmental research. This review examines the relevance, applications, and benefits of PMWI data, focusing on their practical use and benefits to society rather than the specific techniques or algorithms involved in data processing. Specifically, it assesses the impact of PMWI data on Tropical Cyclone (TC) intensity and structure, global precipitation and extreme events, flood prediction, the effectiveness of tropical storm and hurricane watches, fire severity and carbon emissions, weather forecasting, and drought mitigation. Additionally, it highlights the importance of PMWIs in hydrometeorological and real-time applications, emphasizing their current usage and potential for improvement. Key recommendations from users include expanding satellite networks for more frequent global coverage, reducing data latency, and enhancing resolution to improve forecasting accuracy. Despite the notable benefits, challenges remain, such as a lack of direct research linking PMWI data to broader societal outcomes, the time-intensive process of correlating PMWI use with measurable societal impacts, and the indirect links between PMWI and improved weather forecasting and disaster management. This study provides insights into the effectiveness and limitations of PMWI data, stressing the importance of continued research and development to maximize their contribution to disaster preparedness, climate resilience, and global weather forecasting. Full article

Despite the abundance of available studies on optical and microwave methods devoted to investigating agricultural crop conditions, there is a lack of research that explores the integration between microwave and optical data and the link between photosynthetic activity, measured by PRI (photochemical reflectance index), and vegetation water content, detected by radar sensors. In particular, there is a lack of vision that links these measures to better understand how plants react and adapt to possible water stress conditions. Most of the existing research tends to treat optical and microwave information separately, without investigating how the integration of these techniques can provide a more complete and accurate understanding of the research topic, corroborated by ground data. In this paper, an integrated approach using microwave and optical satellite data, respectively acquired by Sentinel-1 (S-1) and Sentinel-2 (S-2), was presented for monitoring vegetation status. Experimental data and electromagnetic models have been combined to relate backscattering from S-1 and optical indices from S-2 to plant conditions, which were evaluated by measuring PRI, plant water content (PWC), and soil water content. Field data were collected in two sorghum fields close to Florence in Tuscany (Central Italy) during the summers of 2022 and 2023. The results show significant correlations between microwave and optical data with respect to field measurements, highlighting the potential of remote sensing techniques for agricultural monitoring and management, also in response to climate change. Determination coefficients of R² = 0.51 between PRI and PWC, where PWC is retrieved by S-1, and R² = 0.73 between PSRI (plant senescence reflectance index) and PRI were obtained. Full article

Optoelectronic oscillators (OEOs) have emerged as indispensable tools for generating low-phase-noise microwave and millimeter-wave signals, which are critical for a variety of high-performance applications. These include radar systems, satellite links, electronic warfare, and advanced instrumentation. The ability of OEOs to produce signals with exceptionally low phase noise makes them ideal for scenarios demanding high signal purity and stability. In radar systems, low-phase-noise signals enhance target detection accuracy and resolution, while, in communication networks, such signals enable higher data throughput and improved signal integrity over extended distances. Furthermore, OEOs play a pivotal role in precision instrumentation, where even minor noise can compromise the performance of sensitive equipment. This review examines the progress in OEO technology, transitioning from classical designs relying on long optical fiber delay lines to modern integrated systems that leverage photonic integration for compact, efficient, and tunable solutions. Key advancements, including classical setups, hybrid designs, and integrated configurations, are discussed, with a focus on their performance improvements in phase noise, side-mode suppression ratio (SMSR), and frequency tunability. A 20-GHz oscillation with an SMSR as high as 70 dB has been achieved using a classical dual-loop configuration. A 9.867-GHz frequency with a phase noise of −142.5 dBc/Hz @ 10 kHz offset has also been generated in a parity–time-symmetric OEO. Additionally, integrated OEOs based on silicon photonic microring resonators have achieved an ultra-wideband tunable frequency from 3 GHz to 42.5 GHz, with phase noise as low as −93 dBc/Hz at a 10 kHz offset. The challenges in achieving fully integrated OEOs, particularly concerning the stability and phase noise at higher frequencies, are also explored. This paper provides a comprehensive overview of the state of the art in OEO technology, highlighting future directions and potential applications. Full article

Accurate precipitation measurement is critical for managing flood and drought risks. Traditional meteorological tools, such as rain gauges and remote sensors, have limitations in resolution, coverage, and cost-effectiveness. Recently, the opportunistic use of microwave communication signals has been explored to improve precipitation estimation. While there is growing interest in using satellite-to-earth microwave links (SMLs) for machine learning-based precipitation estimation, direct rainfall estimation from raw signal-to-noise ratio (SNR) data via deep learning remains underexplored. This study investigates a range of machine learning (ML) approaches, including deep learning (DL) models and traditional methods like gradient boosting machine (GBM), for estimating rainfall rates from SNR data collected by interactive satellite receivers. We develop real-time models for rainfall detection and estimation using downlink SNR signals from satellites to user terminals. By leveraging a year-long dataset from multiple locations—including SNR measurements paired with disdrometer and rain-gauge data—we explore and evaluate various ML models. Our final models include ensemble approaches for both rainfall detection and cumulative rainfall estimation. The proposed models provide a reliable solution for estimating precipitation using Earth–satellite microwave links, potentially improving precipitation monitoring. Compared to the state-of-the-art power-law-based models applied to similar datasets reported in the literature, our ML models achieve a $46\%$ reduction in the root mean squared error (RMSE) for event-based cumulative precipitation predictions. Full article

Among the essential tools to address global environmental information requirements are the Earth-Observing (EO) satellites with free and open data access. This paper reviews those EO satellites from international space programs that already, or will in the next decade or so, provide essential data of importance to the environmental sciences that describe Earth’s status. We summarize factors distinguishing those pioneering satellites placed in space over the past half century, and their links to modern ones, and the changing priorities for spaceborne instruments and platforms. We illustrate the broad sweep of instrument technologies useful for observing different aspects of the physio-biological aspects of the Earth’s surface, spanning wavelengths from the UV-A at 380 nanometers to microwave and radar out to 1 m. We provide a background on the technical specifications of each mission and its primary instrument(s), the types of data collected, and examples of applications that illustrate these observations. We provide websites for additional mission details of each instrument, the history or context behind their measurements, and additional details about their instrument design, specifications, and measurements. Full article

Multistatic synthetic aperture radar (SAR) is a special mode of SAR system. The radar transmitter and receiver are located on different satellites, which brings many advantages, such as flexible baseline configuration, diverse receiving modes, and more detailed ground object classification information. The multistatic SAR has been widely used in interferometry, moving target detection, three-dimensional imaging, and other fields. The frequency offset between different oscillators will cause a modulation phase error in the signal. Therefore, phase synchronization is one of the most critical problems to be addressed in distributed SAR systems. This article reviews phase synchronization techniques, which are mainly divided into two methods: synchronization by direct microwave link and synchronization by a data-based estimation algorithm. Furthermore, the future development of synchronization technology is anticipated. Full article

Over the past decades, the cryosphere has changed significantly in High Mountain Asia (HMA), leading to multiple natural hazards such as rock–ice avalanches, glacier collapse, debris flows, landslides, and glacial lake outburst floods (GLOFs). Monitoring cryosphere change and evaluating its hydrological effects are essential for studying climate change, the hydrological cycle, water resource management, and natural disaster mitigation and prevention. However, knowledge gaps, data uncertainties, and other substantial challenges limit comprehensive research in climate–cryosphere–hydrology–hazard systems. To address this, we provide an up-to-date, comprehensive, multidisciplinary review of remote sensing techniques in cryosphere studies, demonstrating primary methodologies for delineating glaciers and measuring geodetic glacier mass balance change, glacier thickness, glacier motion or ice velocity, snow extent and water equivalent, frozen ground or frozen soil, lake ice, and glacier-related hazards. The principal results and data achievements are summarized, including URL links for available products and related data platforms. We then describe the main challenges for cryosphere monitoring using satellite-based datasets. Among these challenges, the most significant limitations in accurate data inversion from remotely sensed data are attributed to the high uncertainties and inconsistent estimations due to rough terrain, the various techniques employed, data variability across the same regions (e.g., glacier mass balance change, snow depth retrieval, and the active layer thickness of frozen ground), and poor-quality optical images due to cloudy weather. The paucity of ground observations and validations with few long-term, continuous datasets also limits the utilization of satellite-based cryosphere studies and large-scale hydrological models. Lastly, we address potential breakthroughs in future studies, i.e., (1) outlining debris-covered glacier margins explicitly involving glacier areas in rough mountain shadows, (2) developing highly accurate snow depth retrieval methods by establishing a microwave emission model of snowpack in mountainous regions, (3) advancing techniques for subsurface complex freeze–thaw process observations from space, (4) filling knowledge gaps on scattering mechanisms varying with surface features (e.g., lake ice thickness and varying snow features on lake ice), and (5) improving and cross-verifying the data retrieval accuracy by combining different remote sensing techniques and physical models using machine learning methods and assimilation of multiple high-temporal-resolution datasets from multiple platforms. This comprehensive, multidisciplinary review highlights cryospheric studies incorporating spaceborne observations and hydrological models from diversified techniques/methodologies (e.g., multi-spectral optical data with thermal bands, SAR, InSAR, passive microwave, and altimetry), providing a valuable reference for what scientists have achieved in cryosphere change research and its hydrological effects on the Third Pole. Full article

Rapid intensification (RI) and eyewall replacement cycles (ERCs) frequently occur in intense tropical cyclones (TCs), often causing rapid, significant changes in intensity and structure. In some TCs, RI and ERCs can occur concurrently or within a short period of one another. This study investigates whether there is a link between RI and ERCs by conducting a statistical analysis of TCs that occurred in the North Atlantic basin from 2015 to 2020. The HURDAT2 dataset was used to detect RI events, while the Morphed Integrated Microwave Imagery archive by the Cooperative Institute for Meteorological Satellite Studies was used to detect ERC events. Three sets of data were constructed from this analysis: TCs with paired RI/ERC events that occurred within 24 h of each other, TCs with RI only, and TCs with ERCs only. Statistics selected for analysis within the constructed datasets were mean duration of phenomena, mean rate of intensification, and mean peak intensity. We performed t-tests to determine the statistical significance of results. The results of this study show that TCs with these paired RI/ERC events often intensified at a faster rate, intensified for longer, and ended up stronger than TCs that only experienced RI or ERCs in isolation. Full article

Establishing an ultra-high-precision link for time–frequency comparisons between satellites and ground stations is critically important. This endeavor is fundamental to the advancement of pioneering space science exploration and the development of a robust space-based time–frequency system featuring ultra-high-precision space atomic clocks. In response to the requirements for assessing the long-term stability of high-precision space atomic clocks, we have designed and implemented a satellite–ground microwave time–frequency comparison system and method based on a three-frequency mode. Ground-based experimental results demonstrate that the equipment layer can achieve a satellite–ground time comparison accuracy better than 0.4 ps (RMS), with the equipment delay stability (ADEV) for all three frequencies being better than 8 × 10⁻¹⁸ at 86,400. By leveraging the ground-based experimental results, we constructed a satellite–ground time–frequency comparison simulation and verification platform. This platform realizes ultra-high-precision satellite–ground time–frequency comparison based on the China Space Station (CSS). After correcting various transmission delay errors, the satellite–ground time comparison achieved an accuracy better than 0.8 ps and an ADEV better than 2 × 10⁻¹⁷ at 86,400. This validation of our novel satellite–ground time–frequency comparison system and method, capable of achieving an 10⁻¹⁷ magnitude stability, is not only a significant contribution to the field of space time–frequency systems but also paves the way for future advancements and applications in space science exploration. Full article

The ACES mission of the European Space Agency combines optical and microwave-based geodetic observation techniques with highly accurate atomic clocks to achieve a new level of accuracy for geodesy and fundamental physics applications. In addition, the combination of two high-precision measurement techniques provides an even more exciting insight into their errors. Fundamental physics is particularly interested in experiments that require high precision between the results of the successive passes of a satellite. An example of such an experiment is the determination of gravitational redshift. Geodesy applications, in contrast, require both high accuracy and precision. Especially for applications like precise ranging or time synchronization, all possible error influences must be characterized and determined with high precision. Therefore, electronic delays of microwave link terminals pose a challenge to achieving high accuracy. They must, therefore, be calibrated, and the stability of the electronic delays must be monitored. While optical observation techniques can be calibrated sufficiently on the ground, the calibration of microwave measurements before a launch is not precise enough, and continuous monitoring is also not possible. In this study, four calibration methods were tested, all based on colocating optical and microwave measurements onboard a satellite and on the ground. The results of two methods achieved the required accuracy of 100 ps for time synchronization, with a mean error and standard deviation of better than 4 ps and 55 picoseconds, respectively. Correlations between the measured parameters were identified, and the impact of the different approaches on accuracy was investigated. It will be shown that the satellite-based colocation of two different geodetic observation techniques has clear advantages, and the calibration results achieved the required accuracy for geodetic applications in this simulation study. Full article

This review paper discusses the complete evolution of free-space optical (FSO) communication, also known as unguided optical communication (UOC) technologies, all the way back to ancient man’s fire to today’s machine-learning-supported UOC systems. The principles, significance, and developments that have happened over the past several decades, as well as installation methodologies, technological limitations, and today’s challenges of UOCs are presented. All the subsets of UOC: FSO communication, underwater optical wireless communication (UOWC), and visible light communication (VLC), with their technology/system developments, potential applications, and limitations are reviewed. The state-of-the-art developments/achievements in (i) FSO channel effects and their mitigation techniques; (ii) radio-over-FSO techniques; (iii) wavelength division multiplexing and sub-carrier multiplexing techniques; (iv) FSO for worldwide interoperability for microwave access applications; (v) space optical satellite communication (SOSC); (vi) UWOC; (vii) photoacoustic communication (PAC); (viii) light-fidelity; (ix) VLC; (x) vehicular VLC (V²LC); and (xi) optical camera communication are reviewed. In addition, the current developments on emerging technologies such as artificial intelligence (to improve the performance of UOC systems), energy harvesting (for the effective utilization of UOC channels), and near-future communication network scenarios (mandatory for secured broadband digital links) are covered. Finally, in brief, to achieve the full potential of UOC systems, challenges that require immediate research attention are summarized. Full article

Today, the internet is fundamental to social inclusion. There are many people that live in remote areas, and the only way to supply internet services is through the use of microwave terrestrial and satellite systems. Thus, it is important to have efficient tools to design and optimize these systems. In this paper, a tool with the objective to shorten the time spent in the design process of microwave terrestrial and satellite point-to-point links is presented. This tool can be applied in academia by engineering students, providing an extended analysis of many sections of a link project design, as well as in professional practice by telecommunication engineering departments, presenting a concise step-by-step interactive design process. This tool uses three-dimensional world visualization, with the Cesium Application Programming Interface (API), to display and analyze site-specific characteristics that can disrupt the link’s quality of service (QoS). Using this visualization, two ray-tracing algorithms were developed to analyze signal diffraction and reflection mainly throughout terrestrial links. Using this new algorithm, an innovative process for signal diffraction and reflection calculations was created. Using updated standards provided by the International Telecommunication Union Radiocommunication Sector (ITU-R), the characteristics of the defined simulated links could be predicted, thus providing the user with the metrics of signal quality and system link budget. Full article

In the climate change scenario the world is facing, extreme weather events can lead to increasingly serious disasters. To improve managing the consequent risks, there is a pressing need to have real-time systems that provide accurate monitoring and possibly forecasting which could help to warn people in the affected areas ahead of time and save them from hazards. The oblique earth-space links (OELs) have been used recently as a method for real-time rainfall detection. This technique poses two main issues related to its indirect nature. The first one is the classification of rainy and non-rainy periods. The second one is the determination of the attenuation baseline, which is an essential reference for estimating rainfall intensity along the link. This work focuses mainly on the first issue. Data referring to eighteen rain events were used and have been collected by analyzing a satellite-to-earth link quality and employing a tipping bucket rain gauge (TBRG) properly positioned, used as reference. It reports a comparison among the results obtained by applying four different machine learning (ML) classifiers, namely the support vector machine (SVM), neural network (NN), random forest (RF), and decision tree (DT). Various data arrangements were explored, using a preprocessed version of the TBRG data, and extracting two different sets of characteristics from the microwave link data, containing 6 or 12 different features, respectively. The achieved results demonstrate that the NN classifier has outperformed the other classifiers. Full article

Microwave occultation using centimeter and millimeter wave links between low Earth orbit (LEO) satellites provide a potential way to estimate the moist atmospheric profiles based on refraction and attenuation measurements, which is called the LEO-LEO microwave occultation (LMO) technique. It has not yet been implemented in orbit. In this paper, we analyzed the attenuation properties at different heights of centimeter and millimeter waves based on simulations. The observing capabilities with different frequency combinations at the X, K, and M bands were analyzed. The results show that LMO may improve the retrieval accuracy of bending angles above 35 km. By using several appropriate frequencies at the X+K+M band, water vapor profiles from the near-surface to the lower stratosphere (~24 km) can be obtained. When the M-band frequencies were added, the temperature retrieval accuracy does not change obviously, but the accuracy of water vapor retrieval can significantly improve above 15 km, especially at about 17–24 km, and the RMS errors decrease from over 20% to less 10%. For promoting the LMO mission in the real world, a frequency combination at the X+K band is proposed, which can provide the potential to observe the temperature profiles at about 2.5–50 km and water vapor profiles at about 2.5–15 km accurately under clear and cloudy conditions. This study demonstrates that LMO can greatly extend the capabilities of the radio occultation technique and improve our ability to measure the moist atmospheric profiles globally. Full article