Search Results (67)

The relationship between radar reflectivity (Z) and rainfall intensity (R) plays a crucial role in estimating precipitation and serves as a foundation for flood risk assessment. However, empirical Z–R relationships often introduce considerable uncertainty, making the correction of rainfall estimation errors a key challenge in remote-sensing-based applications. Developing an effective approach to reduce these deviations is, therefore, essential to improve the accuracy of radar-based precipitation measurements. This study aims to develop a methodology for analyzing radar-derived precipitation using dual-polarization radar measurements, with validation based on rain gauge observations. Three well-established Z–R relationships—Marshall–Palmer, Muchnik, and Joss—were applied to radar reflectivity values measured at two heights, 1 km and 1.5 km above ground level. The Marshall–Palmer relationship applied at a height of 1.5 km yielded the smallest deviations from rain gauge measurements. Both the mean absolute error (MAE) and average precipitation difference at this height were consistent, amounting to 1.99 mm, compared to 2.32 mm at 1 km. The range of deviations in all cases was 0.54–7.64 mm at 1.5 km and 0.65–7.18 mm at 1 km. Furthermore, all tested Z–R relationships demonstrated a strong linear correlation with rain gauge data, as indicated by a Pearson correlation coefficient of 0.98. These findings enable the identification of the most accurate Z–R relationships and optimal measurement heights for radar-based precipitation estimation. These results may have important implications for operational applications and the calibration of radar precipitation products. Full article

Weather radars are essential in the Quantitative Precipitation Estimates (QPE) but are susceptible to calibration errors. Previous work demonstrated that observations from the Ku-band Dual Polarization Radar (DPR) radar on board the Global Precipitation Measurement Mission Dual-Precipitation Radar (GPM) are suitable for ground radar calibration. Several studies volume-matched ground radar and GPM DPR Ku-band reflectivities for the absolute calibration of ground radars, by applying different constraints and filters in the volume-matching procedure. This study compares and evaluates volume-matching thresholds and data filtering schemes for the Rizoelia, Larnaca (LCA) and Nata, Pafos (PFO) radars of the Cyprus weather radar network from October 2017 till May 2023. Excluding reflectivities below and within the melting layer with a 250 m buffer yielded consistent results for both ground radars. The selected calibration schemes were combined, and the resulting offsets were compared to stable radar parameters to identify stable calibration periods. The consistency of the wet hydrological year October 2019 to September 2020 suggests that radar calibration results are prone to differences in meteorological conditions, as scarce rainfall can result in insufficient data for reliable calibration. Future work will incorporate disdrometer measurements and extend the analysis to quantitative precipitation estimation. Full article

When frequency-modulated continuous-wave (FMCW) laser radar (Ladar) is employed for three-dimensional imaging, the echo signal is susceptible to modulation nonlinearity and platform vibration due to modulation and the short wavelength. These effects cause main-lobe widening, side-lobe elevation, and positional shift, which degrades distance detection accuracy. To solve these problems, this paper proposes a compensation method combining multiple synchrosqueezing transform (MSST), equal-phase interval resampling, and high-order ambiguity function (HAF). Firstly, variational mode decomposition (VMD) is applied to the optical prism signal to eliminate low-frequency noise and harmonic peaks. MSST is used to extract the time–frequency curve of the optical prism. The nonlinearity in the transmitted signal is estimated by two-step integration. An internal calibration signal containing nonlinearity is constructed at a higher sampling rate to resample the actual signal at an equal-phase interval. Then, HAF compensates for high-order vibration and residual phase error after resampling. Finally, symmetrical triangle wave modulation is used to remove constant-speed vibration. Verifying by actual data, the proposed method can enhance the main lobe and suppress the side lobe about 1.5 dB for a strong reflection target signal. Natural-target peaks can also be enhanced and the remaining peaks are suppressed, which is helpful to extract an accurate target distance. Full article

Sea clutter introduces a significant amount of non-target reflections in the echo signals received by radar, complicating target detection and identification. To address the challenge of existing filter parameters being unable to adapt in real-time to the characteristics of sea clutter, this paper integrates ocean numerical models into the sea clutter spectrum estimation. By adjusting filter parameters based on the spectral characteristics of sea clutter, the accurate suppression of sea clutter is achieved. In this paper, the Weather Research and Forecasting (WRF) model is employed to simulate the ocean dynamic parameters within the radar detection area. Hydrological data are utilized to calibrate the parameterization scheme of the WRF model. Based on the simulated ocean dynamic parameters, empirical formulas are used to calculate the sea clutter spectrum. The filter coefficients are updated in real-time using the sea clutter spectral parameters, enabling precise suppression of sea clutter. The suppression algorithm is validated using X-band radar-measured sea clutter data, demonstrating an improvement factor of 17.22 after sea clutter suppression. Full article

Multistatic imaging systems are commonly used in radar systems and microwave imaging. In these systems, many antennas are arranged three-dimensionally and connected to RF switches. The length of each transmitter (Tx) and receiver (Rx) channel differs slightly, causing artifacts in high-resolution image reconstruction. This study presents a novel method for the phase calibration of multistatic systems. This method does not require system reconstruction and can automatically perform phase calibration in a short time. This method is expected to facilitate an accurate phase measurement in multistatic systems. The approach involves phase calibration by analyzing the reflection coefficients of antenna elements in the time domain. Imaging experiments were performed on a multistatic imaging system using this calibration method, and the position and shape of a metal rod with a diameter one-fourth of a wavelength were reconstructed by simple back-projection with an accuracy beyond the diffraction limit. Full article

With global warming and intensified human activities, extreme convective precipitation has become one of the most frequent natural disasters. An accurate and reliable assessment of severe convective precipitation events can support social stability and economic development. In order to investigate the accuracy enhancement methods and data fusion strategies for the assessment of severe convective precipitation events, this study is driven by the horizontal reflectance factor (Z_H) and differential reflectance (Z_DR) of the dual-polarization radar. This research work utilizes microphysical information of convective storms provided by radar variables to construct the precipitation event assessment model. Considering the problems of high dimensionality of variable data and low computational efficiency, this study proposes a dual-polarization radar echo-data-layering strategy. Combined with the results of mutual information (MI), this study constructs Bayes–Kalman filter (KF) models (RF, SVR, GRU, LSTM) for the assessment of severe convective precipitation events. Finally, this study comparatively analyzes the evaluation effectiveness and computational efficiency of different models. The results show that the data-layering strategy is able to reduce the data dimensions of 256 × 256 × 34,978 to 5 × 2213, which greatly improves the computational efficiency. In addition, the correlation coefficient of interval III–V calibration period is increased to 0.9, and the overall assessment accuracy of the model is good. Among them, the Bayes–KF-LSTM model has the best assessment effect, and the Bayes–KF-RF has the highest computational efficiency. Further, five typical precipitation events are selected for validation in this study. The stratified precipitation dataset agrees well with the near-surface precipitation, and the model’s assessment values are close to the observed values. This study completely utilizes the microphysical information offered by dual-polarized radar Z_H and Z_DR in precipitation event assessment, which provides a wide range of application possibilities for the assessment of severe convective precipitation events. Full article

Dielectric properties are crucial in understanding the behavior of water within soil, particularly the soil water content (SWC), as they measure a material’s ability to store an electric charge and are influenced by water and other minerals in the soil. However, a comprehensive review paper is needed that synthesizes the latest developments in this field, identifies the key challenges and limitations, and outlines future research directions. In addition, various factors, such as soil salinity, temperature, texture, probing space, installation gap, density, clay content, sampling volume, and environmental factors, influence the measurement of the dielectric permittivity of the soil. Therefore, this review aims to address the research gap by critically analyzing the current state-of-the-art dielectric properties-based methods for SWC measurements. The motivation for this review is the increasing importance of precise SWC data for various applications such as agriculture, environmental monitoring, and hydrological studies. We examine time domain reflectometry (TDR), frequency domain reflectometry (FDR), ground-penetrating radar (GPR), remote sensing (RS), and capacitance, which are accurate and cost-effective, enabling real-time water resource management and soil health understanding through measuring the travel time of electromagnetic waves in soil and the reflection coefficient of these waves. SWC can be estimated using various approaches, such as TDR, FDR, GPR, and microwave-based techniques. These methods are made possible by increasing the dielectric permittivity and loss factor with SWC. The available dielectric properties are further synthesized on the basis of mathematical models relating apparent permittivity to water content, providing an updated understanding of their development, applications, and monitoring. It also analyzes recent mathematical calibration models, applications, algorithms, challenges, and trends in dielectric permittivity methods for estimating SWC. By consolidating recent advances and highlighting the remaining challenges, this review article aims to guide researchers and practitioners toward more effective strategies for SWC measurements. Full article

We describe a method to calibrate a Software-Defined Radar (SDRadar) system mounted on an uncrewed aerial vehicle (UAV) with an ultra-wideband (UWB) waveform operated in the near-field region. Radar calibration is a prerequisite for using the full capabilities of the radar system to retrieve geophysical parameters accurately. We introduce a framework and process to calibrate the SDRadar with the UWB waveform in the 675 MHz–3 GHz range in the near-field region. Furthermore, we present the framework for computing the near-field radar cross section (RCS) of an external passive calibration target, a trihedral corner reflector (CR), using HFSS software and with consideration for specific antennas. The calibration performance was evaluated with various distances between the calibration target and radar antennas. The necessity for the knowledge of the near-field RCS to calibrate SDRadar was demonstrated, which sets this work apart from the standard method of using a trihedral CR for backscatter radar calibration. We were able to achieve approximately $0.5$ dB accuracy when calibrating the SDRadar in the anechoic chamber using a trihedral CR. In outdoor field conditions, where the ground rough surface scattering effects are present, the calibration performance was lower, approximately $1.5$ dB. A solution is proposed to overcome the ground effect by elevating the CR above the ground level, which enables applying time-gating around the CR echo, excluding the reflection from the ground. Full article

Radar is an important sensing technology for three-dimensional positioning of aircraft. This method requires detecting the response from the object to the signal transmitted from the antenna, but the accuracy becomes unstable due to effects such as obstruction and reflection from surrounding buildings at low altitudes near the antenna. Accordingly, there is a need for a ground-based positioning method with high accuracy. Among the positioning methods using cameras that have been proposed for this purpose, we have developed a multisite synchronized positioning system using IoT devices equipped with a fish-eye camera, and have been investigating its performance. This report describes the details and calibration experiments for this technology. Also, a case study was performed in which flight paths measured by existing GPS positioning were compared with results from the proposed method. Although the results obtained by each of the methods showed individual characteristics, the three-dimensional coordinates were a good match, showing the effectiveness of the positioning technology proposed in this study. Full article

Ground-penetrating radar (GPR) has been widely used in estimating the permittivity of mediums. The radar echo amplitude method is an important method used by GPR in this estimation, the basic step of which is to deduce the magnitude of the permittivity according to the relationship between the reflection coefficient and the permittivity. Based on the basic principle of the radar echo amplitude method, this paper proposes a full-wave inversion real-time permittivity estimation method that can be used for stepped-frequency GPR (SFGPR), which offers high efficiency, accuracy, and generalization ability. The characteristics of this method are mainly reflected in the following four aspects: Using the SFGPR system and introducing a layered media detection model, we can complete waveform compensation optimization with high precision. The distance between the antenna and the surface of the reflective medium is extracted from the time domain waveform without manual measurement, avoiding human measurement errors. The inversion of the total reflection waveform at the required height works under the principle of an electromagnetic field, eliminating the need for repeated metal plate calibration experiments and improving work efficiency and waveform accuracy. In a continuous measurement line, the total reflection waveform inversion on each measurement point can be efficiently completed, and the change of permittivity on the measurement line can be obtained. To evaluate the feasibility of the proposed method, we performed experiments on a wall of known thickness, and the permittivity estimation was basically consistent with that of the dielectric probe, physical model calculation, and wall penetration. We also successfully applied this method to the dielectric property analysis of adobe samples. The results indicate that the proposed method can help grasp the condition of a measured medium, which can ensure the accuracy of detection and improve subsequent data processing efficiency. Full article

In the complex battlefield electromagnetic environment, multiple jamming signals can enter the radar receiver simultaneously due to the development of jammers and modulation technology. The received compound jamming signals aggravate the difficulty of recognition and subsequent counter-countermeasure. In the face of strong overlapping signals and unseen jamming signal combinations, the performance of existing recognition methods usually seriously degrades. In this paper, an end-to-end multi-label classification framework combining a complex-valued convolutional neural network (CV-CNN) and jamming class representations is proposed to automatically recognize the jamming signal components of compound jamming signals. A basic multi-label CV-CNN (ML-CV-CNN) is first designed to directly process time–domain complex signals and fully retain jamming signal information. Then, the jamming class representations are generated using prototype clustering implemented by learning vector quantization, and they are fused with the ML-CV-CNN using class decoupling implemented by the attention mechanism to construct a multi-label class representation CV-CNN (ML-CR-CV-CNN), which can better learn the class-related features required for recognition. Finally, an adaptive threshold calibration is adopted to obtain optimal recognition results by multi-threshold discrimination. Simulation results verify that the proposed method has superior recognition performance, which is reflected in the strong robustness to the varying jamming-to-noise ratio (JNR) and power ratio, faster convergence speed with high JNRs, and better generalization for unseen jamming signal combinations. Full article

The objective of this study is to test the feasibility of time-lapse GPR measurements for the quality control of repairing operations (i.e., injections) on marble blocks. For the experimental activities, we used one of the preferred repairing fillers (epoxy resin) and some blocks from one of the world’s most famous marble production area (Carrara quarries in Italy). The selected blocks were paired in a laboratory by overlapping one over the other after inserting very thin spacers in order to simulate air-filled fractures. Fractures were investigated with a 3 GHz ground-penetrating radar (GPR) before and after the resin injections to measure the amplitude reduction expected when the resin substitutes the air. The results were compared with theoretical predictions based on the reflection coefficient predicted according to the thin bed theory. A field test was also performed on a naturally fractured marble block selected along the Carrara shore. Both laboratory and field tests validate the GPR as an effective tool for the quality control of resin injections, provided that measurements include proper calibration tests to control the amplitude instabilities and drift effects of the GPR equipment. The method is accurate enough to distinguish the unfilled fractures from the partially filled fractures and from the totally filled fractures. An automatic algorithm was developed and successfully tested for the rapid quantitative analysis of the time-lapse GPR profiles collected before and after the injections. The whole procedure is mature enough to be proposed to the marble industry to improve the effectiveness of repair interventions and to reduce the waste of natural stone reserves. Full article

For triple-frequency radar, the attenuation attributed to atmospheric gases and stratiform clouds is diverse due to different snowfall microphysical properties, particularly in regions far from the radar. When using triple-frequency ground-based radar measurements, evaluating the attenuation of the three radars at different heights is common to derive attenuation-corrected effective reflectivity. Therefore, this study proposes a novel quality-controlled approach to identify radar attenuation due to gases and stratiform clouds that can be neglected due to varying snowfall microphysical properties and assess attenuation along the radar observation path. The key issue lies in the lack of information about vertical hydrometeor and cloud distribution. Therefore, European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data are employed. The Self-Similar-Rayleigh-Gans Approximation (SSRGA) for the nonspherical scattering model in the Passive and Active Microwave TRAnsfer model 2 (PAMTRA2) is compared and analyzed against other scattering models to obtain the optimal triple-frequency radar attenuation correction strategies for stratiform cloud meteorological conditions with varying snowfall microphysical properties. This methodology paves the way for understanding differential attenuation attributed to gas and stratiform clouds with snowfall microphysical properties. Simultaneously, the bin-by-bin approximation method is used to perform the attenuation correction. The two-way attenuation correction increased up to 4.71 dB for heights above 6 km, remaining minimal for regions with heights below 6 km. These values, attributable to gases and stratiform clouds’ two-way attenuation, are nonnegligible, especially at distances far from the W-band radar at heights above 6 km. Both values are relatively small for the X- and Ka-band radars and can be neglected for the varying snowfall microphysical properties. The attenuation correction of triple-frequency radar reflectivity is validated using the cross-calibration and dual-frequency reflectivity ratios. The results show that the method is valid and feasible. Full article

One of the fundamental sensors utilized in the Advanced Driver Assist System (ADAS) is the radar sensor. Automotive-related functions need highly precise detection and range of traffic and surroundings; otherwise, the whole ADAS performance suffers. The radar placement beneath a bumper or a cover, the age or exposure to accidents or vehicle vibration, vehicle integration, and mounting tolerances will impact the angular performance of the radar sensor. In this research, we present an unsupervised online method for elevation mounting angle error compensation and a method for bumper and environmental error compensation in the azimuth direction. The proposed methods need no specific calibration jig and may be used to replace traditional initial calibration methods; they also enable ongoing calibration throughout the sensor’s lifespan. A first proposed standalone method for vertical alignment uses stationary radar targets reflected from the environment to calculate a vertical misalignment angle with a line-fitting algorithm. The vertical mounting error compensation approach delivers two types of correction values: a dynamic value that converges quickly in the case of minor accidents and a more stable correction value that converges slowly but offers a long-term compensation value over the sensor’s lifespan. A second proposed solution uses the vehicle velocity and radar targets properties, like relative velocity and measured azimuth angle, to calculate an individual azimuth correction curve. Real-world data collected from drive testing with a 77 GHz series automobile radar was used to analyze the performance of the proposed methods, yielding encouraging results. Full article

Forest canopy height is an important forest indicator parameter. Synthetic aperture radar tomography (TomoSAR) is an effective method to characterize forest canopy height and describe forest 3D structure; however, the residual phase error of TomoSAR affects the focus of the relative reflectance and can lead to errors in forest canopy height estimation. Therefore, this paper proposes a semi-empirical method to overcome the residual phase effects on forest canopy height estimation. In this study, we used airborne multi-baseline UAVSAR data to estimate forest canopy height via TomoSAR techniques and applied a semi-empirical method to improve forest canopy height estimation without phase calibration to mitigate the effects of phase error. The process is divided into three stages: the first step uses a semi-empirical method to initially determine the optimal relative reflectance loss threshold (K) by excluding the inverse extremes; in the second and third steps, the percentile height was used to gradually reduce the height interval between the upper and lower envelopes to minimize overestimation of extreme values and the lower vegetation. When the root mean square error (RMSE) was minimized, the percentile combinations were determined between the inversion results and a LiDAR dataset of the area. The results show that the canopy height estimation results are not satisfactory when relying solely on the K value to estimate the height difference between the envelope at the top of the forest and the ground; the best result was obtained when K = 0.4, but the corresponding R² value was only 0.13, and the RMSE was 15.23 m. In our proposed method, the K value is determined as 0.3 by excluding the extreme values of the inversion result in the initial step—the corresponding R² and RMSE values were 0.59 and 10.73 m, respectively, representing an RMSE decrease of 29.54% relative to the initial K value. After two steps of correction overestimation, the inversion accuracy was significantly improved with an R² value of 0.65 and an RMSE of 9.69 m, corresponding to an RMSE decrease of 36.38%. Overall, the findings of the study represent an important reference for optimizing future spaceborne TomoSAR forest canopy height estimates. Full article