Geostationary Research Articles

High-fidelity flexible multibody model considering torsional deformation for nonequatorial space elevator

Space elevators are a promising technology for future space transportation. The primary component of a space elevator is a tether deployed from a geostationary orbit towards the Earth and into deep space. Payloads can be transported using a climber moving along the tether. However, obtaining a deeper comprehension of the precise dynamics of a space elevator is challenging. The tether could have various deformations such as elongation, bending, and torsion owing to its flexible nature and the low level of vibration damping in space. Therefore, understanding those effects on the tether is essential for the design concept of a space elevator. Reproducing the behavior of space tether systems on the ground is challenging, which is primarily due to the scale of the system and the difficulty of accurately replicating a space environment. Thus, high-fidelity numerical analysis methods are required to analyze the dynamic response of space elevators precisely. Previously proposed analysis models of space tether systems with climbers have focused on elongation, bending, and rigid body motion of the tether, and the effect of torsional deformation has been neglected. However, a tether can be twisted easily owing to its low torsional stiffness. This study established high-fidelity numerical simulation models for space elevators considering large deformations including the torsion of a tether. This study developed a flexible multibody model with a moving climber using the absolute nodal coordinate formulation with 14 degrees of freedom. Further, the gravitational perturbation caused by the non-sphericity of the Earth was considered. Using the constructed model, the motion and deformation of nonequatorial space elevators caused by the climber motion and the disturbance in the space environment were investigated. The obtained results indicate that gravitational perturbation can induce torsional deformation, particularly at higher anchor latitudes.

A Comparative Analysis of the Effect of Orbital Geometry and Signal Frequency on the Ionospheric Scintillations over a Low Latitude Indian Station: First Results from the 25th Solar Cycle

The equatorial post-sunset ionospheric irregularities induce rapid fluctuations in the phase and amplitude of global navigation satellite system (GNSS) signals which may lead to the loss of lock and can potentially degrade the position accuracy. This study presents a new analysis of L-band scintillation from a low latitude station at Guntur (Geographic 16.44°N, 80.62°E, dip 22.18°), India, for the period of 18 months from August 2021 to January 2023. The observations are categorized either in the medium Earth-orbiting (MEO) or geosynchronous orbiting (GSO) satellites (GSO is considered as a set of the geostationary and inclined geosynchronous satellites) for L1, L2, and L5 signals. The results show a higher occurrence of moderate (0.5 < S4 ≤ 0.8) and strong (S4 > 0.8) scintillations on different signals from the MEO compared to the GSO satellites. Statistically, the average of peak S4 values provides a higher confidence in the severity of scintillations on a given night, which is found to be in-line with the scintillation occurrences. The percentage occurrence of scintillation-affected satellites is found to be higher on L1 compared to other signals, wherein a contrasting higher percentage of affected satellites over GSO than MEO is observed. While a clear demarcation between the L2/L5 signals and L1 is found over the MEO, in the case of GSO, the CCDF over L5 is found to match mostly with the L1 signal. This could possibly originate from the space diversity gain effect known to impact the closely spaced geostationary satellite links. Another major difference of higher slopes and less scatter of S4 values corresponding to L1 versus L2/L5 from the GSO satellite is found compared to mostly non-linear highly scattered relations from the MEO. The distribution of the percentage of scintillation-affected satellites on L1 shows a close match between MEO and GSO in a total number of minutes up to ~60%. However, such a number of minutes corresponding to higher than 60% is found to be larger for GSO. Thus, the results indicate the possibility of homogeneous spatial patterns in a scintillation distribution over a low latitude site, which could originate from the closely spaced GSO links and highlight the role of the number of available satellites with the geometry of the links, being the deciding factors. This helps the ionospheric community to develop inter-GNSS (MEO and GSO) operability models for achieving highly accurate positioning solutions during adverse ionospheric weather conditions.

An adaptive fusion algorithm for coastal sea altimetry based on dual-frequency Beidou-R carrier phase.

This article proposes an integer ambiguity determination method based on Beidou system-reflectometry (Beidou-R) observations of the carrier phase at the B1I and B3I frequencies. To enhance the accuracy of sea surface height (SSH) estimation, this study introduces a parallel filtering algorithm and an adaptive iterative fusion algorithm, enabling data fusion based on the variance at B1I and B3I frequencies. To validate and evaluate the proposed method, a coastal experiment was conducted at the Shenxian River. In this experiment, reflected signals from GEO and IGSO satellites were collected. Data analysis reveals that the method is effective, demonstrating that the root mean square error (RMSE) of SSH achieves 2.85 cm and 2.89 cm for PRN 04 and PRN 33, respectively. Furthermore, the impact of the elevation angle on measurement accuracy is analyzed. This study aims to propose a method to enhance coastal sea surface height estimation, offering potential advancements in sea surface altimetry.

Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign

Abstract. The high temporal resolution of thermal infrared imagery from the Geostationary Operational Environmental Satellites R-series (GOES-R) presents an opportunity to observe mountain snow and forest temperatures over the full diurnal cycle. However, the off-nadir views of these imagers may impact or bias temperature observations, especially when viewing a surface composed of both snow and forests. We used GOES-16 and -17 thermal infrared brightness temperature observations of a flat snow- and forest-covered study site at Grand Mesa, Colorado, USA, to characterize how forest coverage and view angle impact these observations. These two geostationary satellites provided views of the study area from the southeast (134.1° azimuth, 33.5° elevation) and southwest (221.2° azimuth, 35.9° elevation), respectively. As part of the NASA SnowEx field campaign in February 2020, coincident brightness temperature observations from ground-based and airborne IR sensors were collected to compare with those from the geostationary satellites. Observations over the course of 2 cloud-free days spanned the entire study site. The brightness temperature observations from each dataset were compared to find their relative differences and how those differences may have varied over time and/or as a function of varying forest cover across the study area. GOES-16 and -17 brightness temperatures were found to match the diurnal cycle and temperature range within ∼ 1 h and ± 3 K of ground-based observations. GOES-16 and -17 were both biased warmer than nadir-looking airborne IR and ASTER observations. The warm biases were higher at times when the sun–satellite phase angle was near its daily minimum. The phase angle, the angle between the direction of incoming solar illumination and the direction from which the satellite is viewing, reached daily minimums in the morning for GOES-16 and afternoon for GOES-17. In morning observations, warm biases in GOES-16 brightness temperature were greater for pixels that contained more forest coverage. The observations suggest that a “thermal infrared shadow-hiding” effect may be occurring, where the geostationary satellites are preferentially seeing the warmer sunlit sides of trees at different times of day. These biases are important to understand for applications using GOES-R brightness temperatures or derived land surface temperatures (LSTs) over areas with surface roughness features, such as forests, that could exhibit a thermal infrared shadow-hiding effect.

Solar zenith angle-based calibration of Himawari-8 land surface temperature for correcting diurnal retrieval error characteristics

The geostationary Himawari-8 satellite offers a unique opportunity to monitor sub-daily thermal dynamics over Asia and Oceania, and several operational land surface temperature (LST) retrieval algorithms have been developed for this purpose. However, studies have reported inconsistency between LST data obtained from geostationary and polar-orbiting platforms, particularly for daytime LST, which can arise from variations in viewing geometries and inherent differences in sensor types and LST algorithms. Despite this, previous research has primarily focused on analysing the directionality of LST without thoroughly exploring systematic differences between platforms. Hence, we presented a Solar Zenith Angle-based Calibration (SZAC) method to harmonise the daytime component of a split-window retrieved Himawari-8 LST (referred to here as the baseline) with the MODerate-resolution Imaging Spectroradiometer (MODIS) LST. SZAC describes the spatial heterogeneity and magnitude of diurnal LST discrepancies from different platforms, which is anticipated to complement typical directionality analyses. We evaluated the harmonised LST data, referred to as the Australian National University LST with SZAC (ANUSZAC), against MODIS LST and the Visible Infrared Imaging Radiometer Suite (VIIRS) LST, as well as in-situ LST from the OzFlux network. Two peer Himawari-8 LST products from Chiba University and the Copernicus Global Land Service were also collected for comparison. The median daytime bias of ANUSZAC LST against Terra-MODIS LST, Aqua-MODIS LST and VIIRS LST was 1.52 K, 0.98 K and −0.63 K, respectively, which demonstrated improved performance compared to baseline (5.37 K, 4.85 K and 3.02 K, respectively) and Chiba LST (3.71 K, 2.90 K and 1.07 K, respectively). All four Himawari-8 LST products showed comparable performance of unbiased root mean squared error (ubRMSE), ranging from 2.47 to 3.07 K, compared to LST from polar-orbiting platforms. In the evaluation against in-situ LST, the mean values of bias (ubRMSE) of baseline, Chiba, Copernicus and ANUSZAC LST during daytime were 4.23 K (3.74 K), 2.16 K (3.62 K), 1.73 K (3.31 K) and 1.41 K (3.24 K), respectively, based on 171,289 hourly samples from 20 OzFlux sites across Australia between 01/Jan/2016 and 31/Dec/2020. In summary, the SZAC method offers a promising approach to enhance the reliability of geostationary LST retrievals by incorporating the spatiotemporal characteristics observed by accurate polar-orbiting LST data. SZAC can also reduce LST angular effects due to its capability of quantifying spatial inhomogeneity of surface heat dynamics. Furthermore, it is possible to implement SZAC using LST data acquired by geostationary satellites in other regions, e.g., Europe, Africa and Americas. This could improve our understanding of the error characteristics of coincident imageries from geostationary and polar-orbiting platforms, allowing for targeted refinements and global harmonisations to further enhance applicability.

A Lagrangian perspective on the lifecycle and cloud radiative effect of deep convective clouds over Africa

Abstract. The anvil clouds of tropical deep convection have large radiative effects in both the shortwave (SW) and longwave (LW) spectra with the average magnitudes of both over 100 W m−2. Despite this, due to the opposite sign of these fluxes, the net average of the anvil cloud radiative effect (CRE) over the tropics is observed to be neutral. Research into the response of the anvil CRE to climate change has primarily focused on the feedbacks of anvil cloud height and anvil cloud area, in particular regarding the LW feedback. However, tropical deep convection over land has a strong diurnal cycle which may couple with the shortwave component of the anvil cloud radiative effect. As this diurnal cycle is poorly represented in climate models it is vital to gain a better understanding of how its changes impact the anvil CRE. To study the connection between the deep convective cloud (DCC) lifecycle and CRE, we investigate the behaviour of both isolated and organised DCCs in a 4-month case study over sub-Saharan Africa (May–August 2016). Using a novel cloud tracking algorithm, we detect and track growing convective cores and their associated anvil clouds using geostationary satellite observations from the Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI). Retrieved cloud properties and derived broadband radiative fluxes are provided by the Community Cloud retrieval for CLimate (CC4CL) algorithm. By collecting the cloud properties of the tracked DCCs, we produce a dataset of anvil cloud properties along their lifetimes. While the majority of DCCs tracked in this dataset are isolated, with only a single core, the overall coverage of anvil clouds is dominated by those of clustered, multi-core anvils due to their larger areas and lifetimes. We find that the anvil cloud CRE of our tracked DCCs has a bimodal distribution. The interaction between the lifecycles of DCCs and the diurnal cycle of insolation results in a wide range of the SW anvil CRE, while the LW component remains in a comparatively narrow range of values. The CRE of individual anvil clouds varies widely, with isolated DCCs tending to have large negative or positive CREs, while larger, organised systems tend to have a CRE closer to 0. Despite this, we find that the net anvil cloud CRE across all tracked DCCs is close to neutral (−0.94 ± 0.91 W m−2). Changes in the lifecycle of DCCs, such as shifts in the time of triggering, or the length of the dissipating phase, could have large impacts on the SW anvil CRE and lead to complex responses that are not considered by theories of LW anvil CRE feedbacks.

Characterization of Doppler shift in inter-satellite laser link between LEO, MEO, and GEO orbits

Over the past few decades, the development of optical wireless communications (OWC) has led to its application in a wide range of environments, including indoor, outdoor, and space. Optical carriers offer advantages such as high bandwidth, security, and directivity, making it a suitable technology for applications in radio astronomy, remote sensing, cellular networks, high-speed train communications, last-mile access, underwater/terrestrial communications, and satellite communications employing laser links. However, laser links between satellites experience Doppler shift due to their relative motion, and this effect should be taken into account from a system design perspective. This paper presents a study of the Doppler shift characterization in laser links for circular Keplerian orbits. An analytical derivation establishes the relationship between the Keplerian orbital elements and the Doppler shift in laser links. The derived equations provide a more comprehensive understanding of the impact of these orbital elements on the Doppler shift in laser links. Additionally, equations have been derived for the Doppler shift rate and the visibility window condition during satellite communication. Furthermore, we conducted a link failure analysis using simulations to evaluate the effects of the Doppler shift, also identifying the worst-case scenarios for orbits most significantly impacted by this shift. The results showed that among the six Keplerian orbital elements, the semi-major axis, inclination, and right ascension of ascending node contribute to the Doppler shift in circular orbits. While the Doppler shift impact is less significant for laser communication systems employing intensity modulation/direct detection, it can degrade the communication system performance for coherent detection. This work contributes to the effective estimation of Doppler shift from a system design perspective.

The Deep Space Radiation Probe: Development of a first lunar science payload for space environment studies and capacity building

Regions outside of Low Earth Orbit (LEO, altitudes above approximately 1000 km) are classified as “deep space”, including Medium Earth Orbit (MEO), geostationary orbit (GEO), as well as cislunar and lunar space. The deep space environment poses many challenges for human and robotic exploration, including stronger ionizing radiation fluxes, more extreme temperature variations, as well as limited data downlink volume. With the growth of the rideshare and hosted payload model aboard government and commercial lunar missions, developing the capacity to design and implement payloads and other space avionics for this environment is of increased importance this decade. Utilizing one of the growing number of rideshare opportunities offered by commercial lunar mission providers, National Central University (NCU) has been working on the rapid development of Taiwan’s first scientific payload for lunar lander use, with launch aboard the HAKUTO-R Mission 2 (M2) lander from ispace, inc. scheduled not earlier than Q4 2024. This Deep Space Radiation Probe (DSRP) will provide measurements of radiation dose, dose rate, and single event upset (SEU) rate during the Earth-Moon transit, in lunar orbit, as well as on the lunar surface. DSRP utilizes elements of the on-board computer (OBC) developed and flight qualified aboard the NCU-developed IDEASSat 3U CubeSat mission in 2021, and was developed by a student team, in consultation with experienced engineers from the lunar lander team. In this paper, we will report on the objectives, concept of operation, design, and implementation of the DSRP project. We will also describe the steps taken to facilitate parallel development of the DSRP payload and the HAKUTO-R M2 lander, as well as lessons learned during the design, implementation, and qualification process. The radiation data provided by DSRP will be beneficial for the development of future deep space spacecraft avionics, as well as crewed missions, and will also serve to build the capacity for deep space spacecraft and payload development at NCU.

An Adaptive Dual-Mode Task-Oriented Resource Management Strategy for GEO Relay Systems

With the fierce global competition on satellite networks, the building of satellite constellations grows explosively. Sharply increasing on-orbit data will face the challenge of satellite-ground data transmission. GEO satellites become the top choice for satellite data relay due to their stable satellite-ground link. Most existing spectrum resource management for GEO relays is equipment-oriented and benefit priority, which may lead to a waste of spectrum resources. In this paper, we propose a real-time task-oriented resource allocation strategy for GEO relay systems. We model the spectrum allocation problem as a distributed non-cooperative Stackelberg game process. We prove that when both sides of the game pursue the maximization of personal revenue, the system will enter a Nash equilibrium state, whereas spectrum resources are not fully used. Based on the maximization of individual utilities (U-prior) and spectrum utilization (S-prior) methods, we design an adaptive dual-mode pricing mode to maximize the spectrum resources within a certain loss of revenue. The simulation results show that the S-prior and U-prior have better performance than the baseline method and existing optimization methods. Our proposed dual-mode strategy is making more throughputs and has less delay with little loss of utility values than that of individual utility maximization.

Orbit Determination of High Orbit Spacecraft based on BDS-3 using Extended Kalman Filter

The positioning of highly elliptical orbit (HEO) spacecraft is very important in deep space exploration and other missions. The Beidou Navigation Satellite System (BDS-3), which was completed in 2020, has put forward new ideas for using GNSS technology to make up for the lack of earth-based TT&C systems. At the same time, the selection of the gravity field order and the perturbation forces must be considered when using dynamical methods for HEO spacecraft positioning. In this paper, simulation experiments are carried out based on the Two-Line Orbital Element (TLE) data of BDS. Two HEO satellites with different semimajor-axis (67509.6 km, 212857.3 km) are selected as the target spacecraft orbits. The single point positioning (SPP) method and Extended Kalman Filter (EKF) method are used for HEO spacecrafts positioning respectively. The experiments show that a 20×20 order gravity field model can be chosen for the orbital integral of HEO spacecraft orbits, and the integration error caused by solar gravity and lunar gravity should be taken into account with the change of orbital altitude. Adding Geostationary Orbit (GEO) and Inclined GeoSynchronous Orbit (IGSO) navigation satellites improved the visibility of these two orbits by 19.45% and 16.64%, respectively, and improved the GDOP value by 14.1% and 3.8%, respectively, compared to observing MEO satellites only. The use of the EKF method can effectively improve the positioning accuracy of the HEO spacecraft compared to the SPP method. For the spacecraft in HEO-1, the RMS value of the positioning errors of the EKF method was 67.82 m, and the accuracy of each direction was improved by 44.28%, 38.85%, and 38.62%, respectively. For the spacecraft in HEO-2, the positioning errors in the x direction of EKF method was within 12 km and within 2 km in the y and z directions. The accuracy of these three directions was improved by 84.91%, 79.24%, and 58.64%, respectively.

A Systematic Review of the Application of the Geostationary Ocean Color Imager to the Water Quality Monitoring of Inland and Coastal Waters

A Systematic Review of the Application of the Geostationary Ocean Color Imager to the Water Quality Monitoring of Inland and Coastal Waters

Generation of diurnal internal solitary waves (ISW-D) in the Sulu Sea: From geostationary orbit satellites and numerical simulations

Our recent study reported the existence of internal solitary waves with the diurnal tidal cycle (ISW-D) in the Sulu Sea, however, the three-dimensional characteristics and generation mechanism of ISW-D are still unclear (Huang et al., 2023). In this work, the spatial–temporal characteristics, generation mechanism and propagating process of ISW-D in the Sulu Sea are first preliminary investigated based on high-temporal-resolution Geostationary Orbiting Satellite (GOS) images and high-spatial-resolution two-dimensional numerical model (MITgcm). GOS images from 2018-2022 are retrieved and a total of 13 pairs of ISW-D packets are found. ISW-D occur at spring tide during May–August, with an average interpacket distance of 198 km and a phase speed of 2.30 m/s. To further knowledge of the generation mechanism and propagation process of ISW-D, the non-linear and non-hydrostatic numerical simulations are conducted. The comparison of ISW-D parameters with GOS images proves the validity of numerical simulations. The results of numerical simulations and theoretical parameters indicate that ISW-D are generated at the sill near Pearl Bank by internal tide release mechanism. Moreover, three sensitivity experiments are designed to investigate the effects of tidal force and seawater stratification on the generation and propagation of ISW-D. The results reveal that the ISW-D is generated by diurnal tides with stronger intensity than semidiurnal tides. Seawater stratification does not influence the generation of ISW-D but modulates the propagation process. Phase speeds from GOS images and theoretical model show a positive correlation between the phase speeds of ISW-D and the intensity of seawater stratification.

Life Cycle of Precipitating Cloud Systems from Synergistic Satellite Observations: Evolution of Macrophysical Properties and Precipitation Statistics from Geostationary Cloud Tracking and GPM Active and Passive Microwave Measurements

Abstract Observations of clouds and precipitation in the microwave domain from the active dual-frequency precipitation radar (DPR) and the passive Global Precipitation Measurement (GPM) Microwave Imager (GMI) onboard the GPM Core Observatory satellite are used in synergy with cloud tracking information derived from infrared imagery from the GOES-13 and Meteosat-7 geostationary satellites for analysis of the life cycle of precipitating cloud systems, in terms of temporal evolution of their macrophysical characteristics, in several oceanic and continental regions of the tropics. The life cycle of each one of the several hundred thousand cloud systems tracked during the 2-yr (2015–16) analysis period is divided into five equal-duration stages between initiation and dissipation. The average cloud size, precipitation intensity, precipitation top height, and convective and stratiform precipitating fractions are documented at each stage of the life cycle for different cloud categories (based upon lifetime duration). The average life cycle dynamics is found remarkably homogeneous across the different regions and is consistent with previous studies: systems peak in size around midlife; precipitation intensity and convective fraction tend to decrease continuously from the initiation stage to the dissipation. Over the three continental regions, Amazonia (AMZ), central Africa (CAF), and Sahel (SAH), at the early stages of clouds’ life cycle, precipitation estimates from the passive GMI instrument are systematically found to be 15%–40% lower than active radar estimates. By highlighting stage-dependent biases in state-of-the-art passive microwave precipitation estimates over land, we demonstrate the potential usefulness of cloud tracking information for improving retrievals and suggest new directions for the synergistic use of geostationary and low-Earth-orbiting satellite observations.

Simultaneously Adjusting Deployment Strategies for Mega-Constellations Using Low-Thrust Maneuvers

Deploying a constellation can be costly and inefficient. The ultimate goal is to position multiple satellites into designated orbital slots with the fewest launches and lowest energy consumption. This paper presents a method for simultaneous right ascension of the ascending node (RAAN) and argument of latitude (AOL) adjustments using continuous low thrust. Firstly, how changes in the semimajor axis and inclination affect the RAAN and the AOL is analyzed. A control method is proposed, and all satellites are sequentially placed from the injection orbit to the working orbit at specific time intervals. Because the RAAN and AOL are coupled with each other, a priority control strategy is introduced. This strategy ensures that the AOL is accurately satisfied within the time between each maneuver. Next, equations that correlate the RAAN and the AOL with the orbit inclination deviation and maneuver interval time are established. By studying the maneuver time intervals and inclination compensations, a highly accurate synchronized deployment scheme can be obtained. A simulation experiment based on the OneWeb constellation is carried out. In the simulation, 80 satellites are launched by just one rocket. By employing the proposed method, the constellation is successfully deployed. Results from the simulation verified the effectiveness of the proposed algorithm, which may be employed for rapid deployment of a mega-constellation in the future.

Wide and Deep Learning Model for Satellite-Based Real-Time Aerosol Retrievals in China

Machine learning methods have been recognized as rapid methods for satellite-based aerosol retrievals but have not been widely applied in geostationary satellites. In this study, we developed a wide and deep learning model to retrieve the aerosol optical depth (AOD) using Himawari-8. Compared to traditional deep learning methods, we embedded a “wide” modeling component and tested the proposed model across China using independent training (2016–2018) and test (2019) datasets. The results showed that the “wide” model improves the accuracy and enhances model interpretability. The estimates exhibited better accuracy (R2 = 0.81, root-mean-square errors (RMSEs) = 0.19, and within the estimated error (EE) = 63%) than those of the deep-only models (R2 = 0.78, RMSE = 0.21, within the EE = 58%). In comparison with extreme gradient boosting (XGBoost) and Himawari-8 V2.1 AOD products, there were also significant improvements. In addition to higher accuracy, the interpretability of the proposed model was superior to that of the deep-only model. Compared with other seasons, higher contributions of spring to the AOD concentrations were interpreted. Based on the application of the wide and deep learning model, the near-real-time variation of the AOD over China could be captured with an ultrafine temporal resolution.

FY-4A Measurement of Cloud-Seeding Effect and Validation of a Catalyst T&D Algorithm

FY-4A Measurement of Cloud-Seeding Effect and Validation of a Catalyst T&D Algorithm

Deterministic Global 3D Fractal Cloud Model for Synthetic Scene Generation

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to match natural cloud shapes. This model is intended to run quickly, and it can run in about 700 ms per cloud type. This model generates clouds that appear to match large-scale satellite imagery, and it reproduces natural small-scale shapes. This should enable future versions of ASSET to generate scenarios where the same scene is consistently viewed from both GEO and LEO satellites from multiple perspectives.

CSL-SFNet for Cooperative Spectrum Sensing in Cognitive Satellite Network with GEO and LEO Satellites

In a cognitive satellite network (CSN) with GEO and LEO satellites, there is a large propagation losses between the sensing satellite and the ground station. The results of spectrum sensing from a single satellite may be inaccurate, which will create serious interference in the primary satellite system. Cooperative spectrum sensing (CSS) has become the key technology for solving the above problems in recent years. However, most of the current CSS techniques are model-driven. They are difficult to model and implement in CSNs since their detection performance is strongly dependent on an assumed statistical model. Thus, we propose a novel CSS scheme, which uses convolutional neural networks (CNNs), self-attention (SA) modules, long short-term memory networks (LSTMs), and soft fusion networks, called CSL-SFNet. This scheme combines the advantages of CNNs, SA modules, and LSTMs to extract the features of the input signals from the spatial and temporal domains. Additionally, the CSL-SFNet makes use of a novel soft fusion technique that improves detection performance while also considerably reducing communication overhead. The simulation results demonstrate that the proposed algorithm can achieve a detection probability of 90% when the signal-to-noise ratio is −20 dB; it has a shorter running time and always outperforms the other CSS algorithms.

Extraction and analysis of the sea ice parameter dataset of the Bohai Sea from 2011 to 2021 based on GOCI

The Bohai Sea and its surrounding areas are rich in oil and natural gas and play an important role in industry, agriculture and the economy. However, the Bohai Sea suffers severely from sea ice in the winter. While previous research has predominantly focused on methods for retrieving sea ice parameters in the Bohai Sea, analyses of their long-term statistical patterns have been limited. The Geostationary Ocean Color Imager (GOCI) is the first geostationary satellite for ocean color remote sensing, offering high spatial and temporal resolution, which greatly facilitates the extraction of Bohai Sea ice parameters. Utilizing GOCI data, we systematically extracted relevant sea ice parameters for the Bohai Sea region from 2011 to 2021. These parameters include sea ice concentration, sea ice thickness, and sea ice drift. We conducted a comprehensive statistical analysis of the long-term sea ice changes in the Bohai Sea and found that the development process of winter sea ice area is different from the sea ice thickness, and the direction of sea ice drift is basically unchanged. Then we developed statistical models linking sea ice parameters with ocean dynamic factors such as temperature, wind, and drift currents. Among them, the correlation coefficient between the predicted value and the measured value of the sea ice area model is the highest, reaching 0.8382. Furthermore, we examined the previously unexplored relationship between daily sea ice area, sea ice thickness, and accumulated temperature with their respective starting temperatures and accumulation periods. This study provides critical data to support Bohai Sea ice monitoring and marine environmental research. The results of this study contribute to a better understanding of sea ice change trends in the Bohai Sea and inform the development of disaster prevention and mitigation measures.

Simulation of range code tracking loop for multipath mitigation in NavIC receiver

Abstract The Operational Navigation with Indian Constellation (NavIC) comprises seven satellites in the orbit, including three in geostationary orbit (GEO) and four in geosynchronous orbit (GSO). NavIC provides both Standard Positioning Service and Restricted Service, using L5 (1176.45 MHz) and S1 (2492.028 MHz) frequencies, with coverage extending 1500 km around the mainland of India. In an urban canyon, multipath interference severely reduces the precision and reliability of NavIC positioning. Many current multipath mitigation techniques often exhibit high computational requirements or reliance on external assistance. In this paper, a ranging code tracking loop is proposed that can sustain either a late or early branch in contrast to the Narrow-Spacing (NS) correlation technique for mitigating multipath for NavIC receiver. The design of proposed code tracking loop is based on steepest descent algorithm. The findings demonstrate that, in terms of calculation time and code multipath mitigation, the suggested technique performs better than both Multipath Estimated Delay Locked Loop (MEDL) and NS correlation. The proposed method produces less than 0.016 chips for the tracking error Standard Deviation (STD). In addition, the recommended method takes 24 % less computation time.