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Quasi-periodic (QP) emissions are a type of magnetospheric ELF/VLF waves characterized by a periodic intensity modulation ranging from tens of seconds to several minutes. Here, we present 63 QP events observed between January 2017 and December 2018. Initially detected at the VLF receiver in Kannuslehto, Finland (KAN, MLAT = 67.7°N, L = 5.5), we proceeded to check whether these events were simultaneously observed at other subauroral receivers. To do so we used the following PWING stations: Athabasca (ATH, MLAT = 61.2°N, L = 4.3, Canada), Gakona (GAK, MLAT = 63.6°N, L = 4.9, Alaska), Husafell (HUS, MLAT = 64.9°N, L = 5.6, Iceland), Istok (IST, MLAT = 60.6°N, L = 6.0, Russia), Kapuskasing (KAP, MLAT = 58.7°N, L = 3.8, Canada), Maimaga (MAM, MLAT = 58.0°N, L = 3.6, Russia), and Nain (NAI, MLAT = 65.8°N, L = 5.0, Canada). We found that: (1) QP emissions detected at KAN had a relatively longer observation time (1–10 h) than other stations, (2) 11.3% of the emissions at KAN were observed showing one-to-one correspondence at IST, and (3) no station other than IST simultaneously observed the same QP emission as KAN. Since KAN and IST are longitudinally separated by 60.6°, we estimate that the maximum meridional spread of conjugated QP emissions should be close to 60° or 4 MLT. Comparison with geomagnetic data shows half of the events are categorized as type II, while the rest are mixed (type I and II). This study is the first to clarify the longitudinal spread of QP waves observed on the ground by analyzing simultaneous observations over 2 years using multiple ground stations.

Coherent detection provides the optimum performance for free space optical (FSO) communication systems. However, such detection systems are expensive and require digital phase noise compensation. In this paper, the transmission performance of long-haul FSO system for ground-to-satellite communication based on a Kramers–Kronig (KK) transceiver is evaluated. KK transceivers utilize inexpensive direct detection receivers and the signal phase is retrieved from the received current using the well-known KK relations. KK transceivers are not sensitive to the laser phase noise and, hence, inexpensive lasers with large linewidths can be used at the transmitter. The transmission performance of coherent and KK transceivers is compared in various scenarios such as satellite-to-ground, satellite-to-satellite, and ground-to-satellite for weak, moderate, and strong turbulence. The results show that the transmission performance of a system based on the KK transceiver is comparable to that based on a coherent transceiver, but at a significantly lower system cost and complexity. It is shown that in the absence of turbulence, the coherent receiver has a ~3 dB performance advantage over the KK receiver. However, in the presence of strong turbulence, this performance advantage becomes negligible.

Popular small satellites host individual sensors or sensor networks in space but require ground stations with directional antennas on rotators to download sensors’ data. Such ground stations can establish a single downlink communication with only one satellite at a time with high vulnerability to system outages when experiencing severe channel impairments or steering engine failures. To contribute to the area of improving the reception quality of small satellites signals, this paper presents a simple receive diversity scheme with proposed processing algorithms to virtually combine satellite downlink streams collected from multiple omnidirectional receivers. These algorithms process multiple received versions of the same signal from multiple geographically separated receiving sites to be combined in one virtual ground station. This virtual ground station helps detect the intended signal more reliably based only on a network of simple and cooperating software-defined radio receivers with omnidirectional antennas. The suggested receive diversity combining techniques can provide significant system performance improvement if compared to the performance of each individual receiving site. In addition, the probability of system outages is decreased even if one or more sites experience severe impairment consequences. Simulation results showed that the bit error rate (BER) of the combined stream is lower than the BER of the best quality receiving site if considered alone. Moreover, virtual ground stations with cooperative omnidirectional reception at geographically separated receivers also allow data to be received from multiple satellites in the same frequency band simultaneously, as software-defined receivers can digitize a wider portion of the frequency band. This can be a significant conceptual advantage as the number of small satellites transmitting data grows, and it is reasonable to avoid the corresponding necessary increase in the number of fully equipped ground stations with rotators.

Urban rail transit, a convenient and fast public transportation mode with rapid construction and development, occupies fewer land resources and accommodates large passenger volumes. However, thermal comfort should be given more attention. Stations above ground level experience poor thermal comfort on the platforms, especially in hot summers. This study combines field research with a simulation analysis to propose a strategy for improving thermal comfort on above-ground urban rail transit platforms. This study analyzed the effects of the skylight opening rate, side window opening rate, design of transparent maintenance structure shading, and the platform profile shape on the thermal comfort of above-ground stations using field research, comparative experiments, and a simulation analysis with the PHOENICS (Command Prompt) software. The results indicate that adding longitudinal sunshade louvers to the skylight of the station platform is a cost-effective method to reduce the average temperature and PMV value, thereby improving thermal comfort. Increasing the skylight opening rate can result in a temperature rise. Adjusting the opening rate of the side windows to 20% and adding sun-shading louvers can also significantly enhance the station’s thermal comfort. Taking Wudaokou Station on Beijing Line 13 as an example, the simultaneous installation of additional longitudinal skylight shading and side window shading and increasing the side window opening rate to 20% on the platform resulted in a 2.6 °C decrease in the average temperature, a 4.7% increase in the average wind speed, and a 0.62 decrease in the PMV value, significantly enhancing thermal comfort for passengers. This study confirms that optimizing shading and ventilation systems can significantly reduce the platform temperature and improve passengers’ thermal comfort. This study provides theoretical support and innovative methods for optimizing thermal environments in similar environments.

This paper studies the performance of the communication link between a ground station and the satellites of a LEO constellation, employing code division multiplexing and a non-linear high-power amplifier. The analysis shows that the input power selection at the high-power amplifier of the ground station has a significant impact on overall system performance. The results concerning output power, the challenge of adjusting the back-off with a continuously changing number of satellites, and improved energy efficiency suggest operating in saturation. In this scenario, we can choose to transmit directly the sign of the sum of the signals directed to individual satellites. Analytical exact and simplified results are derived, enabling the estimation of performance as a function of the number of satellites being served when the amplifier operates at saturation. These analytic results are further validated through simulations. A formula to compute the loss across different numbers of satellites is also presented. The performance under saturated amplifier conditions is evaluated, compared, and discussed, providing valuable insights for simplifying the design and operation of satellite uplink communication systems under power amplifier constraints.

Microsatellites have attracted a large number of scholars and engineers because of their portability and distribution characteristics. The ground station suitable for microsatellite service has become an important research topic. In this paper, we propose a networked ground station and verify it on our own microsatellite. The specific networked ground station system consists of multiple ground nodes. They can work together to complete data transmission tasks with higher efficiency. After describing our microsatellite project, a reasonable distribution of ground nodes is given. A cloud computing model is used to realize the coordination of multiple ground nodes. An adaptive communication system between satellites and ground stations is used to increase link efficiency. Extensive on-orbit experiments were used to validate our design. The experimental results show that our networked ground station has excellent performance in data transmission capability. Finally, the specific cloud-computing-based ground station network successfully completes our satellite mission.

Low Earth orbit (LEO) satellite constellations have emerged as an effective alternative for the provision of high-accuracy positioning, navigation and timing (PNT) solutions which are based on high-precision orbit and clock information. Determining an orbit with high precision is dependent on the number and distribution of ground tracking stations. Therefore, it is important to investigate methodologies that can ensure the adequate observing coverage of LEO navigation constellations. In this study, an evolutionary algorithm is applied to optimize the number and deployment of ground stations for tracking LEO constellations. According to the distribution area, two schemes of study are analyzed: (a) global deployment—the ground stations are deployed throughout the globe; (b) regional deployment—a selected region is used for deployment. For global deployment, the optimization objectives are focused on the ground station and observing rate for k-heavy observing coverage (HC), while the sole objective for the regional deployment scheme is the satellite position dilution of precision (SPDOP). It is shown that a deployment of 95 ground stations is optimal for achieving 3-HC with an observing rate of 97.37% and 4-HC with an observing rate of 92.01%. For regional distribution, 15, 20 and 25 ground stations are used for three optimal configurations of SPDOP at 2.058, 1.399 and 1.330, respectively. The results are significantly enhanced using intersatellite links for SPDOP evaluation, from 2.058, 1.399 and 1.330 to 0.439, 0.422 and 0.409, with 15, 20 and 25 ground stations, respectively.

Space-to-ground laser communication (SGLC) offers a paradigm-shifting solution to overcome the bandwidth constraints of radio frequency systems by leveraging laser beams for ultra-high data throughput, although its link availability probability is significantly affected by atmospheric conditions such as cloud cover. Existing ground station (GS) placement methods decouple site selection from downlink scheduling, failing to effectively quantify the data throughput of candidate sites. This study proposes a data throughput-driven joint optimization framework that integrates downlink scheduling into the site selection model for the first time. Additionally, the site selection model also incorporates equipment cost constraints and service capacity limitations by introducing an integer variable Q to characterize the deployment scale of laser communication terminals (LCTs) at each GS. Through auxiliary variable linearization techniques, the site selection problem is transformed into a tractable integer linear programming (ILP) formulation. A branch-and-bound algorithm is proposed to achieve global optimal solution search. Numerical results demonstrate that the proposed approach improves data throughput compared to the existing method.

Satellites have been developed and operated for various purposes. The global satellite market is growing rapidly as the number of satellites and their mission diversity increase. Satellites revolve around the Earth to perform missions and communicate with ground stations repeatedly and sequentially. However, because satellites are orbiting the Earth, there is a limited time window for missions to a specific area and communication with ground stations. Thus, in an environment where multiple satellites and multiple ground stations (MS-MGs) are operated, scheduling missions and communications to maximize the utilization of satellites is a complex problem. For the MS-MG scheduling problem, this study proposes a mixed-integer linear programming (MILP) model to assign time windows for missions and communications with ground stations to individual satellites. The MILP model is based on the concept of a time-space network and includes constraints reflecting on the space mission environment of satellites. The objective function and constraints of the MILP model were validated through numerical experiments based on actual data from Korean satellites.

Radars with mmWave frequency modulated continuous wave (FMCW) technology accurately estimate the range and velocity of targets in their field of view (FoV). The targeted angle of arrival (AoA) estimation can be improved by increasing receiving antennas or by using multiple-input multiple-output (MIMO). However, obtaining target features such as target type remains challenging. In this paper, we present a novel target classification method based on machine learning and features extracted from a range fast Fourier transform (FFT) profile by using mmWave FMCW radars operating in the frequency range of 77–81 GHz. The measurements are carried out in a variety of realistic situations, including pedestrian, automotive, and unmanned aerial vehicle (UAV) (also known as drone). Peak, width, area, variance, and range are collected from range FFT profile peaks and fed into a machine learning model. In order to evaluate the performance, various light weight classification machine learning models such as logistic regression, Naive Bayes, support vector machine (SVM), and lightweight gradient boosting machine (GBM) are used. We demonstrate our findings by using outdoor measurements and achieve a classification accuracy of 95.6% by using LightGBM. The proposed method will be extremely useful in a wide range of applications, including cost-effective and dependable ground station traffic management and control systems for autonomous operations, and advanced driver-assistance systems (ADAS). The presented classification technique extends the potential of mmWave FMCW radar beyond the detection of range, velocity, and AoA to classification. mmWave FMCW radars will be more robust in computer vision, visual perception, and fully autonomous ground control and traffic management cyber-physical systems as a result of the added new feature.