Spaceborne Radar Research Articles

Assessment of ISRO’s S-band polarimetric Doppler Weather Radar (DWR) at SHAR with IMD-DWR and GPM-Ku radar

ABSTRACT This paper describes the first assessment of ISRO’s indigenously developed S-band Polarimetric Doppler Weather Radar (DWR) at Sriharikota High Altitude Range (SHAR), Sriharikota (13.66°N, 80.23°E). The assessment is done during the passage of a tropical cyclone ‘Phethai’ and four different cases of Mesoscale convective systems. A comparison of reflectivity measured from SHAR-DWR with India Meteorological Department (IMD) DWR located at Chennai (13.07°N, 80.28°E) and Ku-band space-borne radar of the Global Precipitation Mission (GPM) is done using the common volume matching method. A good comparison is observed between SHAR-DWR with IMD-DWR and GPM-Ku radar in both space and height. The vertical structure of the cyclone is provided using Contour Frequency by Altitude Diagrams (CFAD) which show the vertical extent up to an altitude of 16 km with a reflectivity between 25 and 30 dBZ. Maximum occurrence of 30 dBZ occurs below 6 km. Bright band signatures show ~ 25 dBZ between 4 and 5 km depicting the stratiform precipitation of the cyclone. Further rain rate is estimated using both reflectivity and the polarimetric product which compared well with rain estimated from IMD-DWR and rainfall observed from rain gauges. Rain rate is observed from 5 to 35 mm hr−1. Hydrometer classification during the passage of tropical cyclone ‘Phethai’ shows the presence of rain below 4 km and graupels, ice crystals, and large droplets above.

Differences in Thunderstorms' Ice Microphysics Between the Amazon and Central Africa Inferred From Spaceborne Passive Microwave and Radar Observations

AbstractThis study examines the differences related to microphysical properties of ice in thunderstorms over the Amazon and Congo Basin using the Precipitation Feature (PF) data sets derived from passive microwave and radar observations from the Tropical Rainfall Measuring Mission and Global Precipitation Mission Core Satellites. Analysis reveals that Amazon thunderstorms are likely composed of ice crystals smaller but more numerous than those in the Congo Basin, resulting in half as many flashes per PF on average in the Amazon, for similar Ice Water Content (IWC) or Area of 30 dBZ at −10°C (Acharge). The increase of the flash count following an increase of the IWC (Acharge) is only 72% (61%) as effective in the Amazon as it would be in the Congo Basin area. PFs with similar 30 dBZ radar echo top heights exhibit lower Brightness Temperatures (TBs) in the 85/89, 165, and 183 GHz frequencies over the Amazon, indicating more numerous smaller ice particles compared to those over the Congo Basin, which tend to show colder TBs at 37 GHz, possibly due to more numerous large graupel or hail particles. Comparisons of TBs in PFs with similar 30 dBZ echo top temperature between the Amazon and 3 × 3º global grids show that the median TB in Amazon is higher than that in most oceanic areas but is comparable to areas having high oceanic lightning activity (e.g., South Pacific Convergence Zone). It suggests that systems in the Amazon have similarities with maritime precipitation systems, yet with distinct characteristics indicative of land systems.

Remote sensing of soil moisture using Rydberg atoms and satellite signals of opportunity

Spaceborne radar remote sensing of the earth system is essential to study natural and man-made changes in the ecosystem, water and energy cycles, weather and air quality, sea level, and surface dynamics. A major challenge with current approaches is the lack of broad spectrum tunability due to narrow band microwave electronics, that limit systems to specific science variable retrievals. This results in a significant limitation in studying dynamic coupled earth system processes such as surface and subsurface hydrology from a single compact instrument, where co-located broad spectrum radar remote sensing is needed to sense multiple variables simultaneously or over a short duration. Rydberg atomic sensors are highly sensitive broad-spectrum quantum detectors that can be dynamically tuned to cover micro-to-millimeter waves with no requirement for RF band-specific electronics. Rydberg atomic sensors can use existing transmitted signals such as from navigation and communication satellites to enable remote sensing. We demonstrate remote sensing of soil moisture, an important earth system variable, via ground-based radar reflectometry with Rydberg atomic systems. To do this, we sensitize the atoms to XM satellite radio signals and use signal correlations to demonstrate use of these satellite signals for remote sensing of soil moisture.

Structural evaluation of urban bridges in Amsterdam through InSAR-based displacement data

Thousands of bridges worldwide face growing risks due to aging materials, increased traffic loads, and climate change-induced weather extremes. Managing these assets is financially demanding, necessitating prioritisation strategies for interventions. Consequently, innovative approaches are urgently required to evaluate the structural conditions of these bridges continuously and regularly. Recent advancements in space-borne Interferometric Synthetic Aperture Radar (InSAR) technology offer cost-effective remote monitoring capabilities, ensuring extensive coverage and high spatial resolution. Multi Temporal (MT) InSAR techniques enable the reconstruction of millimetre-scale deformation measurements for a large number of assets, opening opportunities for long-term regional-scale monitoring of bridge deformations. However, a major challenge in utilising MT-InSAR-based displacement data operationally is that MT-InSAR analysis reconstructs only the projection of displacements along the satellite Line of Sight (LOS) direction. Due to the typical availability of only two satellite viewing geometries, in most cases the three-dimensional displacement field cannot be fully reconstructed. Consequently, without accounting for the anticipated motion of a given structure and its alignment with respect to the satellite flight path, the actual asset movement is likely to be underestimated, leading to erroneous interpretation. In this paper, we propose a method using the bridge typologies and their associated likely failure mechanisms to derive assumptions regarding expected displacement directions. Then, the information on bridge alignments with respect to the satellite flight direction is used to assess the MT-InSAR sensitivity to the expected displacement directions and define ad-hoc damage indicators. We tested the proposed method on urban bridges in Amsterdam, the Netherlands, using deformation measurements derived from TerraSAR-X data spanning 2011 to 2020. Findings have potential to enhance current procedures for the structural evaluation of bridges.

Elevation bias due to penetration of spaceborne radar signal on Grosser Aletschgletscher, Switzerland

Abstract Digital elevation models (DEMs) from the spaceborne interferometric radar mission TanDEM-X hold a large potential for glacier change assessments. However, a bias is potentially introduced through the penetration of the X-band signal into snow and firn. To improve our understanding of radar penetration on glaciers, we compare DEMs derived from the almost synchronous acquisition of TanDEM-X and Pléiades optical stereo-images of Grosser Aletschgletscher in March 2021. We found that the elevation bias – averaged per elevation bin – can reach up to 4–8 m in the accumulation area, depending on post co-registration corrections. Concurrent in situ measurements (ground-penetrating radar, snow cores, snow pits) reveal that the signal is not obstructed by the last summer horizon but reaches into perennial firn. Because of volume scattering, the TanDEM-X surface is determined by the scattering phase centre and does not coincide with a specific firn layer. We show that the bias corresponds to more than half of the decadal ice loss rate. To minimize the radar penetration bias, we recommend to select DEMs from the same time of the year and over long observation periods. A correction of the radar penetration bias is recommended, especially when combining optical and TanDEM-X DEMs.

Spaceborne Radars for Mapping Surface and Subsurface Salt Pan Configuration: A Case Study of the Pozuelos Salt Flat in Northern Argentina

Spaceborne Radars for Mapping Surface and Subsurface Salt Pan Configuration: A Case Study of the Pozuelos Salt Flat in Northern Argentina

Hybrid SAR-ISAR Imaging for Space Target via 2-D Spectrum and SIHR With Spaceborne Radar

Hybrid SAR-ISAR Imaging for Space Target via 2-D Spectrum and SIHR With Spaceborne Radar

Fusion of Ground-Based and Spaceborne Radar Precipitation Based on Spatial Domain Regularization

Fusion of Ground-Based and Spaceborne Radar Precipitation Based on Spatial Domain Regularization

Development of a Full-Scale Connected U-Net for Reflectivity Inpainting in Spaceborne Radar Blind Zones

Abstract CloudSat’s Cloud Profiling Radar is a valuable tool for remotely monitoring high-latitude snowfall, but its ability to observe hydrometeor activity near the Earth’s surface is limited by a radar blind zone caused by ground clutter contamination. This study presents the development of a deeply supervised U-Net-style convolutional neural network to predict cold season reflectivity profiles within the blind zone at two Arctic locations. The network learns to predict the presence and intensity of near-surface hydrometeors by coupling latent features encoded in blind zone-aloft clouds with additional context from collocated atmospheric state variables (i.e., temperature, specific humidity, and wind speed). Results show that the U-Net predictions outperform traditional linear extrapolation methods, with low mean absolute error, a 38% higher Sørensen–Dice coefficient, and vertical reflectivity distributions 60% closer to observed values. The U-Net is also able to detect the presence of near-surface cloud with a critical success index (CSI) of 72% and cases of shallow cumuliform snowfall and virga with 18% higher CSI values compared to linear methods. An explainability analysis shows that reflectivity information throughout the scene, especially at cloud edges and at the 1.2-km blind zone threshold, along with atmospheric state variables near the tropopause, are the most significant contributors to model skill. This surface-trained generative inpainting technique has the potential to enhance current and future remote sensing precipitation missions by providing a better understanding of the nonlinear relationship between blind zone reflectivity values and the surrounding atmospheric state. Significance Statement Snowfall is a critical contributor to the global water–energy budget, with important connections to water resource management, flood mitigation, and ecosystem sustainability. However, traditional spaceborne remote monitoring of snowfall faces challenges due to a near-surface radar blind zone, which masks a portion of the atmosphere. In this study, a deep learning model was developed to fill in missing data across these regions using surface radar and atmospheric state variables. The model accurately predicts reflectivity, with significant improvements over conventional methods. This innovative approach enhances our understanding of reflectivity patterns and atmospheric interactions, bolstering advances in remote snowfall prediction.

River Water Level and Water Surface Slope Measurement From Spaceborne Radar and LiDAR Altimetry: Evaluation and Implications for Hydrological Studies in the Ganga River

River Water Level and Water Surface Slope Measurement From Spaceborne Radar and LiDAR Altimetry: Evaluation and Implications for Hydrological Studies in the Ganga River

Error modeling and hierarchical Bayesian fusion for spaceborne and ground radar rainfall data

The optimal fusion of multisource rainfall data can improve the accuracy and resolution of a posteriori estimates, which is beneficial for hydrological and meteorological applications. In this study, the errors of ground-based dual-polarization radar (GR) and dual-frequency precipitation radar (DPR) on global precipitation measurement (GPM) satellite rainfall estimation were modeled, and a hierarchical Bayesian (HB) framework was developed for GR and DPR rainfall data fusion. According to the matched optimal estimated GR rainfall and rain gauge data, the GR rainfall error was analyzed, and the error variance varying with rain type and intensity was described and modeled. The rain types were classified based on disdrometer and dual-polarization radar data. By comparing the DPR rainfall product with GR rainfall, the DPR rainfall error was divided into systematic and random errors. The systematic error was linearly fitted, and the probability distributions for the random error and the variable error parameters were analyzed and modeled. Because the parameters for GR and DPR rainfall errors varied with rain type and intensity, we developed a HB fusion approach considering the varying parameters in rainfall error modeling. The performance of the fusion algorithm was evaluated using matched GR and DPR cases, which showed that the HB fusion can effectively improve the consistency between the original DPR rainfall product and rain gauge data, reducing the relative bias by an average of 30% and improving the correlation by an average of 20%. Compared with the conventional Bayesian (CB) fusion algorithm, which is based on overall error modeling, the HB fusion results can improve the root mean square error by an average of 24% and relative bias by 14%.

The Doppler Characteristics of Sea Echoes Acquired by Motion Radar

The Doppler characteristics of sea surface echoes reflect the time-varying characteristics of the sea surface and can be used to retrieve ocean dynamic parameters and detect targets. On airborne, spaceborne and shipborne radar platforms, radar moves along with the platforms while illuminating the sea surface. In this case, the area of the sea surface illuminated by radar beam changes rapidly with the motion, and the coherence of the backscattered echoes at different times decreases significantly. Therefore, the Doppler characteristics of the echoes would also be affected by the radar motion. At present, the computational requirements needed to simulate the Doppler spectrum of the microwave scattering field from the sea surface based on numerical methods are huge. To overcome this problem, a new method based on the sub-scattering surface elements has been proposed to simulate the Doppler spectrum of sea echoes acquired by a moving microwave radar. A comparison with the results evaluated by the SSA demonstrate the availability and superiority of the new method proposed by us. The influences induced by radar motion, radar beamwidth, incident angle, and thermal noise on the Doppler characteristics are all considered in this new method. The simulated results demonstrate that the spectrum bandwidth of sea surface echoes acquired by radar on the dive staring motion platform becomes somewhat narrower.

Range-Ambiguous Sea Clutter Suppression for Multichannel Spaceborne Radar Applications Via Alternating APC Processing

In this article, a novel range ambiguous cluter suppression method, i.e., alternating azitmuth phase coding (AAPC), based on azimuth phase coding (APC) is proposed, where the blind areas of target detection are solved. Based on the motion model of spaceborne radar (SBR) system, the sea clutter motion property is analyzed, and a multichannel sea clutter signal model with the consideration of range ambiguity is established. After that, the novel method AAPC is proposed. Finally, a time-domain sliding window projection method with the consideration of clutter internal motions is proposed to realize the sea clutter rejection. Compared with the current range-ambiguous sea clutter suppression algorithms, the improvements of this method are: 1) the range-ambiguous clutter can be separated and most of the clutter components in the main-lobe region can be rejected; and 2) the repetitive detection blind regions can be avoided by applying the proposed AAPC technique. Simulation results are presented to validate the feasibility of the proposed algorithm.

Advancements in Spaceborne Synthetic Aperture Radar Imaging with System-on-Chip Architecture and System Fault-Tolerant Technology

With the continuous development of satellite payload and system-on-chip (SoC) technology, spaceborne real-time synthetic aperture radar (SAR) imaging systems play a crucial role in various defense and civilian domains, including Earth remote sensing, military reconnaissance, disaster mitigation, and resource exploration. However, designing high-performance and high-reliability SAR imaging systems that operate in harsh environmental conditions while adhering to strict size, weight, and power consumption constraints remains a significant challenge. In this paper, we introduce a spaceborne SAR imaging chip based on a SoC architecture with system fault-tolerant technology. The fault-tolerant SAR SoC architecture has a CPU, interface subsystem, memory subsystem, data transit subsystem, and data processing subsystem. The data processing subsystem, which includes fast Fourier transform (FFT) modules, coordinated rotation digital computer (CORDIC) modules (for phase factor calculation), and complex multiplication modules, is the most critical component and can achieve various modes of SAR imaging. Through analyzing the computational requirements of various modes of SAR, we found that FFT accounted for over 50% of the total computational workload in SAR imaging processing, while the CORDIC modules for phase factor generation accounted for around 30%. Therefore, ensuring the fault tolerance of these two modules is crucial. To address this issue, we propose a word-length optimization redundancy (WLOR) method to make the fixed-point pipelined FFT processors in FFT modules fault tolerant. Additionally, we propose a fault-tolerant pipeline CORDIC architecture utilizing error correction code (ECC) and sum of squares (SOS) check. For other parts of the SoC architecture, we propose a generic partial triple modular redundancy (TMR) hardening method based on the HITS algorithm to improve fault tolerance. Finally, we developed a fully automated FPGA-based fault injection platform to test the design’s effectiveness by injecting errors at arbitrary locations. The simulation results demonstrate that the proposed methods significantly improved the chip’s fault tolerance, making the SAR imaging chip safer and more reliable. We also implemented a prototype measurement system with a chip-included board and demonstrated the proposed design’s performance on the Chinese Gaofen-3 strip-map continuous imaging system. The chip requires 9.2 s, 50.6 s, and 7.4 s for a strip-map with 16,384 × 16,384 granularity, multi-channel strip-map with 65,536 × 8192 granularity, and multi-channel scan mode with 32,768 × 4096 granularity, respectively, and the system hardware consumes 6.9 W of power to process the SAR raw data.

Integrating RF MEMS Switch on Array Antenna to Achieve Reconfigurability in Wideband Application

Reconfigurable multi-band antennas are highly used for commercial as well as military purposes as a single antenna could be reconfigured dynamically to send and the receive multiple signals of different frequency simultaneously. In this work an antenna array is designed and integrated with RF MEMS shunt capacitive switch over it, for the applications of S,C,X-band in the frequency range of 2-12GHz. A membrane that can move freely over a coplanar waveguide serves as the MEMS switch. Here, a double meander tuned dual beam arrangement is used to increase switch isolation. Electrostatic mechanisms are used for actuators due to their low power requirements, compact design, and quick switching. By the simulation result, The beam starts to bend from 0.60793mm to 0.4116mm at the voltage 1.78492mV to 57.7382mV and it provides capacitance at 1.435pF to 1.597nF. It was noticed that the insertion loss (S21) and the return loss (S11) of a MEMS switch are around -0.079 dB and 20.618 dB correspondingly, in order to have a good switching characteristic in the up state. The switch has an insertion loss (S21) of -31.307 dB and return loss (S11) of about -0.256 dB in the up state thus exhibiting good switch characteristics. The RF MEMS shunt capacitive switch is integrated on the predesigned antenna array the dynamically shifting of the switch from on state to off state helps achieving the reconfigurability in the antenna array. Such antennas are applicable in spaceborne radar, communication satellites, unmanned aerial vehicles, unmanned aircraft system and various other communication as well as sensing applications.

Multi-source monitoring data helps revealing and quantifying the excavation-induced deterioration of rock mass

There exist many high-steep rock slopes in Southwest China due to the construction of large-scale hydropower projects. The study on excavation-induced damage of high rock slopes is vital for disaster prevention and mitigation. Due to the complexity of high-steep rock slopes, assessing the excavation-induced deterioration of rock mass is often challenging. This study used the space-borne Interferometric synthetic aperture radar (InSAR) and multipoint displacement meters to monitor the slope displacements before and after the excavation. Based on the multi-source monitoring data and the parameter estimation method, we evaluated the changes in rock mass properties due to slope excavation. We employed an improved particle swarm optimization algorithm with dynamic topology and adaptive parameter adjustment and a neural network-based surrogate model in the parameter estimation. The degradation of rock mass strength and stiffness coincides with the increased sensitivity of slope deformation to rainfall infiltration. An in-depth analysis indicates that the absence of vegetation protection and excavation-induced deterioration of rock masses are responsible for the noticeable slope deformation during the rainy season. As slope excavation profoundly influences slope stability and deformation, we should pay closer attention to the excavation way and support style. This study also demonstrates the benefits of using multi-source monitoring data in slope deformation analysis. The findings can aid in comprehending the deformation evolution and instability mechanisms of rock slopes excavated at the hydropower sites, thereby contributing to the prevention and mitigation of landslide disasters.

Moon Imaging Performance of FAST Radio Telescope in Bistatic Configuration with Other Radars

Ground-based radar has been used for Moon imaging for more than 60 years. Five-hundred-meter Aperture Spherical radio Telescope (FAST), as the largest radio telescope on Earth, holds significant potential for celestial imaging missions with its exceptional sensitivity. A bistatic Synthetic Aperture Radar (SAR) Moon imaging model that incorporates FAST and other transmitting radars is presented. The objective of this paper is to design the imaging parameters of this bistatic configuration based on the required resolution, and to estimate the resolution performance based on a given bistatic system capability. Considering the ultra-far range and the ultra-long observation time between the radars and the Moon, the geometric relationship involved in this bistatic configuration is significantly distinct from the bistatic configuration of airborne and spaceborne radars. Therefore, this paper accurately derives the two-dimensional resolution on the Moon’s surface. First of all, the models of the Earth’s surface and the Moon’s surface, and the celestial motion of the Earth and Moon are established using WGS-84 and JPL-DE421, given by STK. Secondly, the bistatic range history within the observation time is calculated in terms of continuous celestial motion instead of the popular ‘stop-and-go’ assumption. Thirdly, no approximation is used in the resolution derivation process, and, in addition to the two-dimensional resolutions, the incident angle and the included angle are also given to describe the imaging performance. This method can also be extended to other bistatic-station and single-station celestial imaging, providing support for radar location and parameters design, for observation time span selection, for observation area selection, and for imaging performance estimation. The echo generation and imaging for point targets set on the Moon are shown. The simulation results prove the validity and accuracy of the proposed method in the paper.

Post-Event Surface Deformation of the 2018 Baige Landslide Revealed by Ground-Based and Spaceborne Radar Observations

On 11 October and 3 November 2018, two large landslides occurred in Baige Village, Tibet, China, forcing the Jinsha River to be cut off and form a dammed lake, resulting in massive economic damages and deaths. This paper uses ground-based radar (GBR) and spaceborne interferometric synthetic aperture radar (InSAR) technologies to perform dynamic monitoring of the Baige landslide. Firstly, the GBR results suggest that the cumulative deformation from 4 to 10 December 2018 was 1.4 m, and the landslide still exhibits a risk of instability. Secondly, with the Sentinel-1A ascending and descending orbit images from December 2018 to February 2022, the InSAR-stacking technology assisted by the generic atmospheric correction online service (GACOS) and the multidimensional small baseline subset (MSBAS) method are utilized to obtain the annual deformation velocity and cumulative deformation in the satellite radar line of sight (LOS) direction of the landslide. Finally, according to the spatial–temporal deformation characteristics of feature points, combined with optical images, field investigation, and geological conditions, the development trend and inducing factors of the Baige landslide are comprehensively analyzed. It is shown that the Baige landslide is in constant motion at present, and the deformation is spreading from the slope to its right side. This research establishes a framework of combining emergency monitoring (i.e., GBR) with long-term monitoring (i.e., spaceborne InSAR). The framework is more conducive to obtaining the deformation and evolution of landslides, providing a greater possibility for studying the development trend and risk assessment of landslides, and assisting in reducing or even avoiding the losses caused by landslides.

Comparative Application of Rain Gauge, Ground- and Space-Borne Radar Precipitation Products for Flood Simulations in a Dam Watershed in South Korea

This study presents a comparative analysis of flood simulations using rain gauge, ground- and space-borne radar precipitation products. The objectives are to assess the effectiveness of two radar-based data sources, namely the Radar-AWS Rainrates (RAR) and Integrated Multi-satellite Retrievals for GPM (IMERG), in a dam watershed with gauge observations, and explore the modeling feasibility of integrating the half-hourly IMERG satellite precipitation in regions with ungauged or limited observational area. Two types of HEC-HMS models were developed, considering areal-averaged and spatially distributed gridded data simulations utilizing eight selected storm events. The findings indicate that the RAR data, although slightly underestimate precipitation compared to the gauge measurements, accurately reproduce hydrographs without requiring parameter adjustments (Nash–Sutcliffe efficiency, ENS, 0.863; coefficient of determination, R2, 0.873; and percent bias, PBIAS, 7.49%). On the other hand, flood simulations using the IMERG data exhibit lower model efficiency and correlation, suggesting potential limitations in ungauged watersheds. Nevertheless, with available discharge data, the calibrated model using IMERG shows prospects for utilization (ENS 0.776, R2 0.787, and PBIAS 7.15%). Overall, this research offers insights into flood simulations using various precipitation products, emphasizing the significance of reliable discharge data for accurate hydrological modeling and the need for further evaluation of the IMERG product.

Spatial Distributions of Cloud Occurrences in Terms of Volume Fraction as Inferred from CloudSat and CALIPSO

The cloud amount, referred to as the frequency of cloud occurrences, is of great importance for the Earth–atmosphere system. It was conventionally quantified as the area fraction of clouds in a given region, discarding the three-dimensional nature of both cloud entities and their spatial distribution. Although the area fraction is explicit, it is the volume fraction that fully depicts cloud occurrences, and the area fraction is just related to a projection of the volume fraction. In this study, by using spaceborne radar measurements, the spatial distribution of cloud volume fraction throughout the troposphere was investigated, and the contributions of various cloud types at each location were clarified. Overall, the volume fraction of total clouds in the whole troposphere is 15.9%, while the corresponding area fraction relative to the global surface is 73.6%. The peak volume fraction occurs at 1 km altitude, mainly contributed by stratocumulus and cumulus. For a single cloud type, the maximum fraction is 48.8%, which is from stratocumulus and occurs at 1 km altitude above the Greenland Sea. Half of the eight cloud types, altostratus, cirrus, nimbostratus, and deep convective clouds, reach the nominal tropopause. In particular, the vertical distribution difference among multiple cloud types in each category (low-level, middle-level, and vertically extending) was clarified, and it was found that the dominant cloud type in a category varies notably with the location in the atmosphere.