Search Results (583)

Elevation Digital Beamforming (DBF) technology is key to achieving high-resolution wide-swath (HRWS) imaging in spaceborne Synthetic Aperture Radar (SAR) systems. However, multi-channel DBF-SAR systems face a prominent conflict between the need for real-time channel error calibration and the constraints of limited on-board hardware resources. To address this bottleneck, this paper proposes a real-time channel error calibration method based on Fast Fourier Transform (FFT) pulse compression and introduces a “calibration-operation” dual-mode control with a parameter-persistence architecture. This scheme decouples high-complexity computations by confining them to the system initialization phase, enabling on-board, real-time, closed-loop compensation for multi-channel signals with low resource overhead. Test results from a high-performance Field-Programmable Gate Array (FPGA) platform demonstrate that the system achieves high-precision compensation for inter-channel amplitude, phase, and time-delay errors. In the 4-channel system validation, the DBF synthesized signal-to-noise ratio (SNR) improved by 5.93 dB, reaching a final SNR of 44.26 dB. This performance approaches the theoretical ideal gain and significantly enhances the coherent integration gain of multi-channel signals. This research fully validates the feasibility of on-board, real-time calibration with low resource consumption, providing key technical support for the engineering robustness and efficient data processing of new-generation SAR systems. Full article

The rapid development of Low Earth Orbit Position, Navigation, and Timing (LEO-PNT) constellations presents opportunities to augment Global Navigation Satellite Systems (GNSSs) with additional signals from Low Earth Orbit (LEO) satellites, thereby improving performance and reliability for users. This research study addresses the challenges posed by the interdependency between LEO and GNSS layers, which can lead to cascading faults. By extending Receiver Autonomous Integrity Monitoring (RAIM)-like capabilities to spaceborne receivers, specifically through Timing Receiver Autonomous Integrity Monitoring (T-RAIM), this paper aims to mitigate these risks. This study validates the integration of T-RAIM with advanced Precise Real-Time On-board Orbit Determination (P2OD) techniques in LEO scenarios using a hardware-in-the-loop test environment. The findings demonstrate that the architecture with T-RAIM can maintain nominal positioning and timing accuracy even in the presence of GNSS clock faults, ensuring continuous system functionality without requiring P2OD restarts. This capability is crucial to preventing service interruptions and enhancing the robustness of LEO-PNT solutions. The proposed integration handles the computational load and complexity while accommodating the limited resources of spaceborne receivers, offering a viable and robust LEO-PNT solution. The experimental results show that T-RAIM effectively mitigates the impact of pseudorange ramp errors, maintaining stable clock bias and preserving the integrity of orbit determination and time synchronization. Full article

With the accelerated launch of spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) satellites, GNSS-R has gradually emerged as an important technique for remote sensing. However, due to its pseudo-random observation mode, the use of a single system makes it difficult to provide continuous spatiotemporal coverage over a specific area within the short term. Although interpolation methods can partially alleviate the coverage gaps, their application is limited by accuracy and reliability constraints, which still restrict the practical use of GNSS-R in terrestrial surface monitoring. To address this issue, conducting joint analyses and data fusion of multi-satellite GNSS-R observations has become an important approach to improving the continuity and accuracy of surface monitoring. However, systematic studies on the integration of multi-satellite GNSS-R data remain relatively limited. Moreover, differences in orbital inclination, antenna design, and signal bandwidth among various spaceborne GNSS-R systems lead to discrepancies in their land observations. Therefore, this study systematically analyzes the reflectivity differences among multiple GNSS-R satellites (e.g., the Cyclone Global Navigation Satellite System (CYGNSS), Fengyun-3 (FY-3), and Tianmu-1 (TM-1)) under consistent surface roughness and land cover conditions, with the aim of providing a theoretical and methodological foundation for the fusion and integrated application of multi-satellite GNSS-R data. The results show that, except for desert regions, the spatial distribution of the correlation coefficients from the least squares fitting of reflectivity between different spaceborne GNSS-R satellites exhibits a pattern similar to that of an established variable, i.e., the vegetation–roughness composite variable (VR), with higher inter-system correlations occurring in areas characterized by lower VR values. Significant reflectivity deviations were observed near water bodies and river networks, such as the Amazon, Paraná, Congo, Niger, Nile, Ganges, Mekong, and Yangtze, where both the fitting intercepts and biases are relatively large. In addition, the reflectivity correlations between CYGNSS–TM-1 and CYGNSS–FY-3 are both strongly influenced by surface vegetation cover type. As the correlation increases, the proportion of non-vegetated and forested areas decreases, while that of grasslands, shrublands, and cropland/vegetation mosaics increases. Analysis of inter-system reflectivity correlations across different land cover types indicates that forested areas exhibit low-to-moderate correlations but maintain stable structural characteristics, whereas wooded areas show moderate correlations slightly lower than those of forests. Grasslands, shrublands, and croplands are mainly distributed within regions of moderate surface roughness and correlation, among which croplands have the highest proportion of highly correlated grids, demonstrating the greatest potential for multi-source data fusion. Wetlands display high roughness and low correlation, largely influenced by dynamic water variations, while bare soils show low roughness (0.2–0.4) but still weak correlations. Full article

A major scientific challenge is understanding how precipitation systems will change under global warming. In particular, extreme precipitation events associated with hail and graupel are of significant concern. In this study, we evaluated the performance of the flagGraupelHail product from the Dual-Frequency Precipitation Radar (DPR) aboard the GPM Core Observatory using high-resolution dual-polarization observations from Multi-Parameter Phased Array Weather Radar (MP-PAWR). The analysis focused on a convective system that developed in a humid environment over the Tokyo region of Japan, providing a valuable assessment within a climatic regime that has been underrepresented in previous studies. A bias correction for MP-PAWR reflectivity, derived from XRAIN network comparisons, yielded good agreement with KuPR observations from the DPR. A new grid-matching method, suitable for comparing vertically varying hydrometeor particle types and available only for MP-PAWR, was also introduced. The comparison revealed that DPR flagGraupelHail detections generally corresponded to regions of graupel occurrence identified by the MP-PAWR GHratio, defined as the number of graupel/hail grids within a DPR observation volume, although DPR tended to detect fewer events. To improve detection performance, we introduced a new indicator, STH35-FH—the height difference between the 35 dBZ echo top and the 0 °C level—as a complementary parameter to the PTI value used to determine flagGraupelHail. Incorporating STH35-FH improved the consistency between DPR and MP-PAWR detections, reducing false positives and enhancing overall detection accuracy. These results demonstrate the value of combining ground-based and spaceborne radar observations to improve global precipitation retrievals, particularly in humid environments. This approach will contribute to more accurate global graupel/hail estimation by spaceborne precipitation radar and a better understanding of how global warming affects precipitation systems. Full article

During orbital operations, spaceborne microstrip antennas are continuously exposed to solar radiation and the cold thermal sink of space, enduring extreme temperature variations. These extreme temperature variations induce significant thermal stress, which leads to deformation in spaceborne antennas, inevitably degrading their operational performance. To address this issue, an optimized design method for antenna array structure based on strain compensation is proposed in this paper. The proposed method uses the COMSOL Multiphysics 6.2 to analyze thermal-structural-electromagnetic coupling behavior of spaceborne microstrip arrays under extreme temperature conditions. The simulation quantifies the thermal-strain distribution. Accordingly, different slits are introduced in regions of high-strain concentration, effectively redistributing the strain to minimize thermal deformation. This optimized configuration maintains superior electrical performance while significantly enhancing thermal stability. Both simulation and measurement results verify the effectiveness of the proposed optimization design method. Notably, the proposed method offers a novel solution for mitigating thermal-induced performance degradation in spaceborne antenna systems without requiring active thermal control. Full article

The ATLAS lidar on NASA’s Earth-orbiting ICESat-2 satellite has operated continuously since its launch in September 2018, with no sign of degradation. Compared to previous international single-beam spaceborne lidars, which operated at a few tens of Hz, the single-photon-sensitive, six-beam ATLAS pushbroom lidar provides 60,000 surface measurements per second and has accumulated almost 3 trillion surface measurements during its six years of operation. It also features a 0.5 m² telescope aperture and a single, 5 Watt, frequency-doubled Nd:YAG laser generating a 10 KHz train of 1.5-nanosecond pulses at a green wavelength of 532 nm. The current paper investigates how, with minor modifications to the ATLAS lidar, this capability might be extended to other planets within our solar system. Crucial to this capability is the need to minimize the solar background seen by the lidar while simultaneously providing, for long time intervals (multiple months), an uninterrupted, modestly powered, multimegabit per second interplanetary laser communications link to a terminal in Earth orbit. The proposed solution is a pair of Earth and planetary satellites in high, parallel, quasi-synchronized orbits perpendicular to their host planet’s orbital planes about the Sun. High orbits significantly reduce the time intervals over which the interplanetary communications link is blocked by their host planets. Initial establishment of the interplanetary communications link is simplified during two specific time intervals per orbit when the sunlit image of the two planets are not displaced from their actual positions (“zero point ahead angle”). In this instance, sunlit planetary images and the orbiting satellite laser beacon can be displayed on the same pixelated detector array, thereby accelerating the coalignment of the two communication terminals. Various tables in the text provide insight for each of the eight planets regarding the impact of solar distance on the worst-case Signal-to-Noise Ratio (SNR), the effect of satellite orbital height on the duration of the unblocked interplanetary communications link, and the resulting planetary surface continuity and resolution in both the along-track and cross-track directions. For planets beyond Saturn, the laser power and/or transmit/receive telescope apertures required to transmit multimegabit-per-second lidar data back to Earth are major challenges given current technology. Full article

Doppler scatterometers have demonstrated the ability to measure wide-swath ocean surface currents from airborne platforms. Since platform velocities for spaceborne platforms are almost two orders of magnitude larger, errors in the knowledge of the pointing of the radar antenna result in ocean current errors that are also two orders of magnitude larger, and this presents a major challenge to achieving useful measurements of ocean currents. Here, we present a new calibration method to estimate pointing biases that removes the dominant pointing errors, allowing for the retrieval of global ocean currents with modest requirements for system stability. The method uses the fact that pointing errors have a velocity signature that depends on cross-track distance (or azimuth angle) alone, while ocean currents do not, if averaged sufficiently along-track. This lack of correlation between error and true currents allows the use of along-track averages of residual radial velocity, after possibly subtracting prior estimates of the currents, for the inversion of the slowly varying pointing errors. The calibration method can be implemented in ground processing and does not impact the processing of onboard data. We illustrate the performance of the calibration on the performance of the proposed NASA/CNES ODYSEA Doppler scatterometer and assess its ability to meet the mission science goals. Full article

Ground-based weather radars are essential to better understand precipitation systems, to improve the Quantitative Precipitation Estimation (QPE), and to subsequently provide input to hydrological models. However, reflectivity measured by radars is typically affected by various sources of uncertainty, including attenuation and calibration errors. Due to these limitations, the two ground-based X-band weather radars of Cyprus, namely, at Rizoelia (LCA) and Nata (PFO), have not yet been employed for QPE. This study presents a dual neural network framework with the ultimate goal of converting the ground-based radar raw reflectivity to rainfall rate, using satellite and in situ observations. The two ground-based radars are aligned with GPM DPR using the volume-matching method. Preliminary results demonstrate the feasibility of converting raw ground-based radar reflectivity to rainfall estimates using neural networks trained with spaceborne and in situ observations. Full article

As the demand for high-speed space-borne data transmission grows, CubeSat-based Free-Space Optical Communication (FSOC) offers a viable solution for achieving a Gbps-speed optical intersatellite link on low-cost platforms. The Very-High-Speed Intersatellite Optical Link System Using an Infrared Optical Terminal and Nanosatellite (VISION) mission aims to establish these high-speed laser crosslinks, which require a precise pointing and relative positioning system at relative distances up to 1000 km. A real-time relative navigation system was developed based on dual-frequency GPS pseudorange and carrier-phase measurements, incorporating an adaptive Kalman filter which uses innovation-based covariance matching to dynamically adjust process noise covariance. Hardware-integrated testing with GPS signal generators and onboard receivers validated its performance under realistic conditions, consistently achieving sub-meter positioning accuracy across baselines up to 1000 km. An integrated orbit–attitude simulation further evaluated the feasibility of the Pointing, Acquisition, and Tracking (PAT) system by combining real-time relative navigation outputs with an attitude control system. Simulation results showed that the PAT system maintained a total pointing error of 274.3 μrad, sufficient to sustain stable high-speed optical links. This study demonstrates that the VISION relative navigation and pointing systems, integrated within the PAT framework, enable precise real-time optical intersatellite communication using CubeSats. Full article

The range-dependence on polarization distortion of spaceborne polarimetric synthetic aperture radar (SAR) affects the accuracy of wide-swath polarization applications, such as environmental monitoring, sea ice classification and ocean wave inversion. Traditional calibration methods, assessing the distortion mainly based on ground experiments, suffer from tedious active calibrator deployment work, which are time-consuming and cost-intensive. This paper proposes a novel polarimetric assessment and calibration method for the quad-polarized wide-swath ScanSAR imaging mode. Firstly, by using distributed target data that satisfy the system reciprocity requirement, we assess the polarization distortion matrices for a single beam in the mode. Secondly, we transfer the matrix results from one beam to another by analyzing data from the overlapping region between beams. Thirdly, we calibrate the quad-polarized data and achieve an overall assessment and calibration results. Compared to traditional calibration methods, the presented method focuses on using cross-beam (overlapping area) data to reduce the dependence on active calibrators and avoid conducting calibration work beam-by-beam. The assessment and calibration experiment is conducted on Gaofen-3 quad-polarized ScanSAR experiment mode data. The calibrated images and polarization decomposition results are compared with those from well-calibrated quad-polarized Stripmap mode data located in the same region. The results of the comparison revealed the effectiveness and accuracy of the proposed method. Full article

Real-time lossless image compression based on the JPEG-LS algorithm is in high demand for critical missions such as satellite remote sensing and space exploration due to its excellent balance between complexity and compression rate. However, few researchers have made appropriate modifications to the JPEG-LS algorithm to make it more suitable for high-speed hardware implementation and application to Bayer pattern data. This paper addresses the current limitations by proposing a real-time lossless compression system specifically tailored for Bayer pattern images from spaceborne cameras. The system integrates a hybrid encoding strategy modified from JPEG-LS, combining run-length encoding, predictive encoding, and a non-encoding mode to facilitate high-speed hardware implementation. Images are processed in tiles, with each tile’s color channels processed independently to preserve individual channel characteristics. Moreover, potential error propagation is confined within a single tile. To enhance throughput, the compression algorithm operates within a 20-stage pipeline architecture. Duplication of computation units and the introduction of key-value registers and a bypass mechanism resolve structural and data dependency hazards within the pipeline. A reorder architecture prevents pipeline blocking, further optimizing system throughput. The proposed architecture is implemented on a XILINX XC7Z045-2FFG900C SoC (Xilinx, Inc., San Jose, CA, USA) and achieves a maximum throughput of up to 346.41 MPixel/s, making it the fastest architecture reported in the literature. Full article

Spaceborne Synthetic Aperture Radar (SAR) has become an indispensable tool for environmental monitoring, offering all-weather, day-and-night imaging capabilities. Before the launch, accurately analyzing the imaging characteristics of spaceborne SAR systems on the ground is crucial, and the antenna system is a very important part of SAR system simulation. This paper investigates the impact of antenna configuration on SAR imaging characteristics by using 3D antenna pattern, focusing on resolution consistency, coverage uniformity, and system adaptability under varying observation geometries. Different from the traditional SAR simulation with 2D antenna pattern (range direction and azimuth direction antenna pattern), we provide a novel simulation method by using 3D antenna pattern, which increases the simulation accuracy and realism. The two mainstream spaceborne SAR antennas (phased array antenna (PAA) and reflector antenna (RA)) are used to illustrate the differences between 2D antenna pattern and 3D antenna pattern. We provide a comparative analysis in the context of high-resolution and wide-swath imaging missions. Additionally, the importance of integrating 3D antenna pattern into SAR system simulation is emphasized, as it improves simulation fidelity, reduces development risk, and supports design validation. This study provides insights for the design and optimization of future SAR system simulation. Full article

Non-cooperative spatial target detection plays a vital role in enabling autonomous on-orbit servicing and maintaining space situational awareness (SSA). However, due to the limited computational resources of onboard embedded systems and the complexity of spaceborne imaging environments, where spacecraft images often contain small targets that are easily obscured by background noise and characterized by low local information entropy, many existing object detection frameworks struggle to achieve high accuracy with low computational cost. To address this challenge, we propose YOLO-GRBI, an enhanced detection network designed to balance accuracy and efficiency. A reparameterized ELAN backbone is adopted to improve feature reuse and facilitate gradient propagation. The BiFormer and C2f-iAFF modules are introduced to enhance attention to salient targets, reducing false positives and false negatives. GSConv and VoV-GSCSP modules are integrated into the neck to reduce convolution operations and computational redundancy while preserving information entropy. YOLO-GRBI employs the focal loss for classification and confidence prediction to address class imbalance. Experiments on a self-constructed spacecraft dataset show that YOLO-GRBI outperforms the baseline YOLOv8n, achieving a 4.9% increase in mAP@0.5 and a 6.0% boost in mAP@0.5:0.95, while further reducing model complexity and inference latency. Full article

Monitoring freshwater resources is essential for assessing the impacts of drought, water management and global warming. Spaceborne LiDAR altimeters allow researchers to obtain water height information, while water area and precipitation data can be obtained using different satellite systems. In our study, we examined 5 years (2018–2022) of data concerning the Euphrates–Tigris Basin (ETB), one of the most important freshwater resources of the Middle East, and the water bodies of both the ETB and the largest lake of Türkiye, Lake Van. A multi-sensor study aimed to detect and monitor water levels and water areas in the water scarcity basin. The ATL13 product of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was used to determine water levels, while the normalized difference water index was applied to the Sentinel-2 optical imaging satellite to monitor the water area. Variations in both water level and area may be related to the time series of precipitation data from the ECMWF Reanalysis v5 (ERA5) product. In addition, our results were compared with global HydroWeb water level data. Consequently, it was observed that the water levels in the region decreased by 5–6 m in many reservoirs after 2019. It is noteworthy that there was a decrease of approximately 14 m in the water level and 684 km² in the water area between July 2019 and July 2022 in Lake Therthar. Full article

Spectroscopic observations of Earth-like exoplanets and ultra-faint galaxies–top scientific priorities for the coming decades–involve measuring broadband signals at rates of only a few photons per square meter per hour. This imposes exceptional requirements on the detector performance, necessitating dark currents below 1 e⁻/pixel/kilo second, read noise under 1 e⁻/pixel/frame, and the ability to handle large-format arrays–capabilities that are not yet met by most existing infrared detectors. In addition, spaceborne LiDAR systems require photodetectors with exceptional sensitivity, compact size, low power consumption, and multi-channel capability to facilitate long-range range finding, topographic mapping, and active spectroscopy without increasing the instrument burden. MCT Avalanche photodiodes arrays offer high internal gain, pixelation, and photon-counting performance across SW to MW wavelengths needed for multi-beam and multi-wavelength measurements, marking them as a critical enabling technology for next-generation planetary and Earth science LiDAR missions. This work reports the latest progress in developing Hg_1−xCd_xTe linear-mode e-APDs at premier industrial research institutions, including relevant experimental data, simulations and major project planning. Related studies are summarized to demonstrate the practical and iterative approach for device fabrication, which have a transformative impact on the evolution of this discipline. Full article