Search Results (114)

The primary payload onboard the Gaofen-3-02 (GF3-02) satellite is a C-band Synthetic Aperture Radar (SAR) capable of achieving a maximum resolution of 1 m. This instrument is critical to monitor the marine environment, particularly for tracking sea surface wind speeds, an important marine environmental parameter. In this study, we utilized 192 sets of GF3-02 SAR data, acquired in Quad-Polarization Strip I (QPSI) mode in March 2022, to retrieve sea surface wind speeds. Prior to wind speed retrieval for vertical-vertical (VV) polarization, radiometric calibration accuracy was analyzed, yielding good performance. The results showed a bias and root mean square errors (RMSEs) of 0.02 m/s and 1.36 m/s, respectively, when compared to the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis V5 (ERA5) data. For horizontal–horizontal (HH) polarization, two types of polarization ratio (PR) models were introduced based on the GF3-02 SAR data. Combining these refitted PR models with CMOD5.N, the results for HH polarization exhibited a bias of −0.18 m/s and an RMSE of 1.25 m/s in comparison to the ERA5 data. Regarding vertical–horizontal (VH) polarization, two linear models based on both measured normalized radar cross sections (NRCSs) and denoised NRCSs were developed. The findings indicate that denoising significantly enhances the accuracy of wind speed measurements for VH polarization when dealing with low wind speeds. When compared against buoy data, the wind speed retrieval results demonstrated a bias of 0.23 m/s and an RMSE of 1.77 m/s. Finally, a comparative analysis of the above retrieval results across all three polarizations was conducted to further understand their respective performances. Full article

Mapping soil organic carbon (SOC) plays a crucial role in agricultural productivity and water management. This study discusses the potential of active and passive remote sensing for SOC estimation modeling in agricultural areas, incorporating synthetic aperture radar (SAR) data (L-band quad-polarization and C-band dual-polarization), multi-spectrum (MS) data, and brightness temperature (TB) data. The performance of five advanced machine learning regression (MLR) models for SOC modeling was assessed, focusing on spatial interpolation accuracy and cross-spatial transfer accuracy, using two field observation datasets for modeling and validation. Results indicate that the SOC estimation accuracy when using MS data alone is comparable to that of using TB data alone, and both perform slightly better than SAR data. Radar cross-polarization ratio index, microwave polarization difference index, shortwave infrared reflectance, and soil parameters (elevation and soil moisture) demonstrate high correlation with the measured SOC. Incorporating temporal features, as opposed to single-phase features, allows each regression model to reach its upper limit of SOC estimation accuracy. The spatial interpolation accuracy of each MLR algorithm is satisfactory, with the Gaussian process regression (GPR) model demonstrating optimal modeling performance. When SAR, MS, or TB data are used individually in modeling, the estimation errors (RMSE) for SOC are 0.637 g/kg, 0.492 g/kg, and 0.229 g/kg for the SMAPVEX12 sampling campaign, and 0.706 g/kg, 0.454 g/kg, and 0.474 g/kg for the SMAPVEX16-MB sampling campaign, respectively. After incorporating soil moisture and topographic factors, the above RMSEs for SOC are further reduced by 57.8%, 35.6%, and 3.5% for the SMAPVEX12, and by 18.4%, 8.8%, and 3.4% for the SMAPVEX16-MB, respectively. However, cross-spatial transfer accuracy of the regression models remains limited (RMSE = 0.866–1.043 g/kg and 0.995–1.679 g/kg for different data sources). To address this, this study reduces uncertainties in SOC cross-spatial transfer by introducing terrain factors sensitive to SOC (RMSE = 0.457–0.516 g/kg and 0.799–1.198 g/kg for different data sources). The proposed SOC estimation and transfer framework, based on active and passive remote sensing data, provides guidance for high-resolution regional-scale SOC mapping and applications. Full article

Quad-polarization synthetic aperture radar (SAR) satellites are important detection tools in Earth observation and remote sensing; in particular, they are of great significance for accurately interpreting radar data and inverting geophysical parameters. Polarimetric calibration is particularly critical to eliminate the effects of distortion in polarized SAR data. The C-SAR/02 satellite launched by China is an important part of the C-band synthetic aperture radar (SAR) constellation, and the quad-polarization strip I (QPSI) is an important imaging mode for its sea–land observation. The relevant research on its polarimetric calibration is still lacking. This study’s polarimetric calibration of C-SAR/02 was performed based on the active radar calibrator (ARC) method using four independently developed L/S/C multi-band ARCs and several trihedral corner reflectors (CRs). The polarimetric calibration distortion matrix varies along the range direction; the polarimetric calibration distortion matrix and polarimetric calibration accuracy along the range direction were analyzed, incorporating the devices in different range directions to calculate the distortion matrix. This approach improved the accuracy of the polarimetric calibration results and the effect of the quantization application of the C-SAR satellites. Moreover, our experimental results indicate that the method presented herein is suitable for the C-SAR/02 satellite and may also be more universally applicable to C-SAR-series satellites. Full article

Tidal marshes play a globally critical role in carbon and hydrologic cycles by sequestering carbon dioxide from the atmosphere and exporting dissolved organic carbon to connected estuaries. These ecosystems provide critical habitat to a variety of fauna and also reduce coastal flood impacts. Accurate characterization of tidal marsh inundation dynamics is crucial for understanding these processes and ecosystem services. In this study, we developed remote sensing-based inundation classifications over a range of tidal stages for marshes of the Mid-Atlantic and Gulf of Mexico regions of the United States. Inundation products were derived from C-band and L-band synthetic aperture radar (SAR) imagery using backscatter thresholding and temporal change detection approaches. Inundation products were validated with in situ water level observations and radiometric modeling. The Michigan Microwave Canopy Scattering (MIMICS) radiometric model was used to simulate radar backscatter response for tidal marshes across a range of vegetation parameterizations and simulated hydrologic states. Our findings demonstrate that inundation classifications based on L-band SAR—developed using backscatter thresholding applied to single-date imagery—were comparable in accuracy to the best performing C-band SAR inundation classifications that required change detection approaches applied to time-series imagery (90.0% vs. 88.8% accuracy, respectively). L-band SAR backscatter threshold inundation products were also compared to polarimetric decompositions from quad-polarimetric Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2) and L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) imagery. Polarimetric decomposition analysis showed a relative shift from volume and single-bounce scattering to double-bounce scattering in response to increasing tidal stage and associated increases in classified inundated area. MIMICS modeling similarly showed a relative shift to double-bounce scattering and a decrease in total backscatter in response to inundation. These findings have relevance to the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission, as threshold-based classifications of wetland inundation dynamics will be employed to verify that NISAR datasets satisfy associated mission science requirements to map wetland inundation with classification accuracies better than 80% at 1 hectare spatial scales. Full article

As a polarimetric synthetic aperture radar (SAR) mode capable of simultaneously acquiring abundant surface information and conducting large-width observations, compact polarimetric synthetic aperture radar (CP SAR) holds great promise for mangrove dynamics monitoring. Nevertheless, there have been no studies on mangrove identification using CP SAR. This study aims to explore the potential of C-band CP SAR for mangrove monitoring applications, with the objective of identifying the most effective CP SAR descriptors for mangrove discrimination. A systematic comparison of 52 well-known CP features is provided, utilizing CP SAR data derived from the reconstruction of C-band Gaofen-3 quad-polarimetric data. Among all the features, Shannon entropy (SE), a random polarimetric constituent (V_B), Shannon entropy (SE_I), and the Bragg backscattering constituent (V_G) exhibited the best performance. By combining these four features, we designed three supervised classifiers—support vector machine (SVM), maximum likelihood (ML), and artificial neural network (ANN)—for comparative analysis experiments. The results demonstrated that the optimal polarimetric feature combination not only reduced the redundancy of polarimetric feature data but also enhanced overall accuracy. The highest accuracy of mangrove extraction reached 98.04%. Among the three classifiers, SVM outperformed the other classifiers in mangrove extraction, while ML achieved the highest overall classification accuracy. Full article

Radar polarimetry is a technique that can be used to enhance target detection, identification and classification; however, the quality of these measurements can be significantly influenced by the characteristics of the radar antenna. For an accurate and reliable system, the calibration of the antenna is vitally important to mitigate these effects. This study presents a methodology to calibrate Ultra-Wideband (UWB) dual-polarised antennas in the near-field using a thin elongated metallic cylinder as the calibration object. The calibration process involves measuring the scattering matrix of the metallic cylinder as it is rotated, in this case producing 100 distinct scattering matrices from which the calibration parameters are derived, facilitating a robust and stable solution. The calibration procedure was tested and validated using a Vector Network Analyser (VNA) and two quad-ridged antennas, which presented different performance levels. The calibration methodology demonstrated notable improvements, aligning the performance of both functioning and under-performing antennas to equivalent specifications. Mid-band validation measurements indicated minimal co-polar channel imbalance (<0.3 dB), low phase error (<0.8°) and improved cross-polar isolation (≈48 dB). Full article

This paper proposes a dual-band patch antenna with combined self-decoupling and filtering properties, designed to suppress mutual coupling between two antenna elements both within the same dual-band and across different dual-bands. Initially, a dual-band aperture-coupled filtering patch antenna is designed, featuring a forked short-circuited SIR feedline with a quarter-wavelength open-ended stub and a U-shaped patch with two U-slots, which generate three controllable radiation nulls while introducing two additional resonant modes. The design steps are also provided in detail. Subsequently, the low mutual coupling phenomenon of two vertically placed aperture-coupled patch antennas is investigated, successfully developing a high-isolated dual-band two-element MIMO array I. Furthermore, the other quad-band two-element MIMO array II is designed, which utilizes the filtering response to significantly reduce mutual coupling across four bands. Finally, a dual-band filtering patch antenna element and two two-element MIMO arrays are fabricated and measured. The measurements and simulations validate the antenna’s low mutual coupling performance in multi-band MIMO arrays and demonstrate its strong potential for future wireless communication applications. Full article

In this work, a novel quad-band rectifier circuit is introduced for RF energy harvesting and Internet of Things (IoT) applications. The proposed rectifier operates in the Wi-Fi frequency band and can supply low-power sensors and systems used in IoT services. The circuit operates at $2.4$, $3.5$, 5, and $5.8$ GHz. The proposed RF-to-DC rectifier is designed based on Delon theory and Greinacher topology on an RT/Duroid 5880 substrate. The results show that our proposed circuit can harvest RF energy from the environment, providing maximum power conversion efficiency (PCE) greater than 81% when the output load is $0.511$ kΩ and the input power is 12 dBm. In this work, we provide a comprehensive design framework for an affordable RF-to-DC rectifier. Our circuit performs better than similar designs in the literature. This rectifier could be integrated into an IoT node to harvest RF energy, thereby proving a green energy source. The IoT node can operate at various frequencies. Full article

This article presents a multiband bandpass filter structure with an in-line topology based on substrate-integrated waveguide (SIW) technology. A multi-layer configuration is employed to achieve circuit miniaturization. By constructing the coupling matrix, the coupling relationships among all resonators are quantitatively characterized, enabling the extraction of the theoretical frequency response and guiding circuit modeling and optimization. We designed and fabricated a third-order tri-band SIW filter and a third-order quad-band SIW filter, achieving a return loss of nearly 20 dB across all passbands. The close agreement between simulated and measured results validates the proposed design model. Additionally, the high in-band isolation of over 40 dB is demonstrated between all adjacent bands, highlighting the potential applicability of this technology in multiband scenarios. Full article

The detection of harbors presents difficulties related to their diverse sizes, varying morphology and scattering, and complex backgrounds. To avoid the extraction of unstable geometric features, in this paper, we propose an unsupervised harbor detection method for polarimetric SAR images using context features and polarimetric reflection symmetry. First, the image is segmented into three region types, i.e., water low-scattering regions, strong-scattering urban regions, and other regions, based on a multi-region Markov random field (MRF) segmentation method. Second, by leveraging the fact that harbors are surrounded by water on one side and a large number of buildings on the other, the coastal narrow-band area is extracted from the low-scattering regions, and the harbor regions of interest (ROIs) are determined by extracting the strong-scattering regions from the narrow-band area. Finally, by using the scattering reflection asymmetry of harbor buildings, harbors are identified based on the global threshold segmentation of the horizontal, vertical, and circular co- and cross-polarization correlation powers of the extracted ROIs. The effectiveness of the proposed method was validated with experiments on RADARSAT-2 quad-polarization images of Zhanjiang, Fuzhou, Lingshui, and Dalian, China; San Francisco, USA; and Singapore. The proposed method had high detection rates and low false detection rates in the complex coastal environment scenarios studied, far outperforming the traditional spatial harbor detection method considered for comparison. Full article

A packaged transmit array (TA) antenna is designed for automotive radar applications operating at 77 GHz. The compact dimensions of the proposed configuration make it compatible with standard quad flat no-lead package (QFN) technology. The TA placed inside the package cover is used to focus the field radiated by a feed placed in the same package. The unit cell of the array is composed of two pairs of stacked patches separated by a central ground plane. A planar patch antenna surrounded by a mushroom-type EBG (Electromagnetic Band Gap) structure is used as the primary feed. An analytical approach is employed to evaluate the primary parameters of the suggested TA, including its directivity, gain and spillover efficiency. The final design has been refined using comprehensive full-wave simulations. The simulated gain is 14.2 dBi at 77 GHz, with a half-power beamwidth of 22°. This proposed setup is a strong contender for highly integrated mid-gain applications in the automotive sector. Full article

In this paper, we present the design of a millimeter-wave 1 × 4 linear MIMO array antenna that operates across multiple resonance frequency bands: 26.28–27.36 GHz, 27.94–28.62 GHz, 32.33–33.08 GHz, and 37.59–39.47 GHz, for mm-wave wearable biomedical telemetry application. The antenna is printed on a flexible substrate with dimensions of 11.0 × 44.0 mm². Each MIMO antenna element features a modified slot-loaded triangular patch, incorporating ‘cross’-shaped slots in the ground plane to improve impedance matching. The MIMO antenna demonstrates peak gains of 6.12, 8.06, 5.58, and 8.58 dBi at the four resonance frequencies, along with a total radiation efficiency exceeding 75%. The proposed antenna demonstrates excellent diversity metrics, with an ECC < 0.02, DG > 9.97 dB, and CCL below 0.31 bits/sec/Hz, indicating high performance for mm-wave applications. To verify its properties under flexible conditions, a bending analysis was conducted, showing stable S-parameter results with deformation radii of 40 mm (Rx) and 25 mm (Ry). SAR values for the MIMO antenna are calculated at 28.0/38.0 GHz. The average SAR values for 1 gm/10 gm of tissues at 28.0 GHz are found to be 0.0125/0.0079 W/Kg, whereas, at 38.0 GHz, average SAR values are 0.0189/0.0094 W/Kg, respectively. Additionally, to demonstrate the telemetry range of biomedical applications, a link budget analysis at both 28.0 GHz and 38.0 GHz frequencies indicated strong signal strength of 33.69 dB up to 70 m. The fabricated linear MIMO antenna effectively covers the mm-wave 5G spectrum and is suitable for wearable and biomedical applications due to its flexible characteristics. Full article

In this demonstration, we present two erbium-doped fiber (EDF) lasers, with series and parallel three sub-ring configurations, respectively, to achieve tunable channel output and stable single longitudinal mode (SLM) operation in the L-band range. Here, the fiber ring cavity contains the L-band EDF as a gain medium. Based on the measured results of the two quad-ring structures of the EDF lasers, tunable output bandwidth for the two lasers can be obtained from 1558.0 to 1618.0 nm simultaneously. All the 3 dB linewidths measured for both fiber lasers are 312.5 Hz over the effective wavelength output range. Furthermore, the related optical signal-to-noise ratio (OSNR), output power, output stabilities of the central wavelength and power, and equal output power range of the two proposed EDF lasers are also examined and discussed. Full article

The role of antennas in wireless communication is critical for enabling efficient signal transmission and reception across various frequency bands, including those associated with IoT (Internet of Things), X-band, S-band, and RFID (radio-frequency identification) systems. This paper presents a small quadruple-band antenna with 25 × 40 × 1.5 mm³ dimensions designed for diverse wireless applications. It is adept at operating in the S-band (2.2 GHz), wireless local area network (WLAN) (5.7 GHz), microwave RFID frequency band (5.8 GHz), and X-band (7.7 GHz and 8.3 GHz). While the majority of existing research focuses on antennas covering two or three bands, our work stands out by achieving quad-band operation in the proposed antenna design. This antenna is constructed on a semiflexible Rogers RT5880 substrate, making it well-suited for wearable applications. Computer Simulation Technology (CST) Microwave studio (2019) simulation package software is chosen for design and analysis. The antenna design features a comb-shaped radiating structure, where each “tooth” is responsible for resonating at a distinct frequency with an appropriate bandwidth. The antenna retains stability in both free space and on-body wearability scenarios. It achieves a low specific absorption rate (SAR), meeting wearable criteria with SAR values below 1.6 W/Kg for all resonating frequencies. The proposed antenna demonstrates suitable radiation efficiency, reaching a maximum of 82.6% and a peak gain of 6.3 dBi. It exhibits a bidirectional pattern in the elevation plane and omnidirectional behavior in the azimuth plane. The antenna finds applications across multiple frequencies and shows close agreement between simulated and measured results, validating its effectiveness. Full article

In this paper, a highly selective quad-band frequency selective surface (FSS) with ultra-wideband rejection is presented. The proposed FSS structure was developed by cascading five metallic layers by three thin dielectric substrates. The five metallic layers are composed of two bent slot layers, two metallic square rings, and a metal patch. The dimensions of the unit cell are 0.13${\lambda }_0$× 0.13${\lambda }_0$× 0.18${\lambda }_0$ (${\lambda }_0$ is the free-space wavelength at the first operating frequency). The proposed structure achieves four transmission bands and has two wide stop-bands located at 1 to 5.5 GHz and 14 to 40 GHz, with a suppressed transmission coefficient below −20 dB. In order to verify the simulation results, an FSS prototype was fabricated and measured. It can be observed that the measured results are in favorable agreement with the simulation results. Its multiple narrow passbands and highly selective and ultra-wideband rejection properties ensure that our design can play a significant role in narrowband antennas, spatial filters, and many other fields. Full article