Radar Field Research Articles

Theoretical Proof and Implementation of Digital Beam Control and Beamforming Algorithm for Low Earth Orbit Satellite Broadcast Signal Reception Processing Terminal

Compared to analog beamforming, digital beamforming offers better self-calibration and lower sidelobe performance, which has a profound impact on improving low Earth orbit receiver performance. The Digital Beamforming (DBF) module in the low Earth orbit satellite broadcast signal reception terminal can use digital phase shifting to compensate for the phase differences caused by path and spatial distance variations due to inconsistent Radio Frequency (RF) channel delays. This compensation ensures in-phase summation, thereby achieving maximum energy reception in the desired direction. Although DBF has gained widespread attention in the radar field due to its unique functions and advantages, its application is limited by beamforming accuracy and gain. Therefore, with the development of DBF technology, how to improve its accuracy and gain has also attracted extensive attention both domestically and internationally. To address this issue, this paper proposes a beamforming method based on a cap-shaped array for low Earth orbit satellite broadcast signal reception and processing terminals. The method combines prior information and spatial domain search for beam control, and employs a lookup table for beam synthesis. It derives formulas for the Signal-to-Noise Ratio, noise figure, processing flow of the beamforming network, and the determination of beamforming weights for the spherical antenna array. The paper presents a beam control approach that combines prior information with spatial domain search, along with an implementation process for beam synthesis using a lookup table. It also details the corresponding Field-Programmable Gate Array (FPGA) implementation process. Finally, the beamforming algorithm is experimentally validated, and error analysis is conducted. The experimental results show that the measured beamforming sensitivity at all incident angles is below −133 dBm and the G/T values are all greater than −9 dB/K, the beam uniformity at three operating frequencies is less than 3°, and the measured errors in pitch and azimuth angles are both below 2°. The beam pointing error is also below 2°.

A Submicrosecond-Response Ultrafast Microwave Ranging Method Based on Optically Generated Frequency-Modulated Pulses.

An ultrafast microwave ranging method based on optically generated frequency-modulated microwave pulses is proposed in this study. The theoretical analysis demonstrated that nanosecond-scale linear frequency modulation microwave pulse can be obtained by femtosecond laser interference under the condition of unbalanced dispersion, which can be used to achieve a high temporal resolution of the displacement change in the measurement by the principle of frequency modulation continuous wave (FMCW) radar. The proof-of-principle experiment successfully measured the displacement change with an error of 2.5 mm and a range of 0.6 m, with a response time of 468 ns. Compared to existing microwave ranging technologies, the temporal resolution was improved by two orders of magnitude, which greatly improves the temporal resolution of distance measurement in the field of microwave FMCW radar.

Local Pyramid Vision Transformer: Millimeter-Wave Radar Gesture Recognition Based on Transformer with Integrated Local and Global Awareness

A millimeter-wave radar is widely accepted by the public due to its low susceptibility to interference, such as changes in light, and the protection of personal privacy. With the development of the deep learning theory, the deep learning method has been dominant in the millimeter-wave radar field, which usually uses convolutional neural networks for feature extraction. In recent years, transformer networks have also been highly valued by researchers due to their parallel processing capabilities and long-distance dependency modeling capabilities. However, traditional convolutional neural networks (CNNs) and vision transformers each have their limitations: CNNs usually overlook the global features of images and vision transformers may neglect local image continuity, and both of them may impede gesture recognition performance. In addition, whether CNN or transformer, their implementation is hindered by the scarcity of public radar gesture datasets. To address these limitations, this paper proposes a new recognition method using a local pyramid visual transformer (LPVT) based on millimeter-wave radar. LPVT can capture global and local features in dynamic gesture spectrograms, ultimately improving the recognition ability of gestures. In this paper, we mainly carried out the following two tasks: building the corresponding datasets and executing gesture recognition. First, we constructed a gesture dataset for training. In this stage, we use a 77 GHz radar to collect the echo signals of gestures and preprocess them to build a dataset. Second, we propose the LPVT network specifically designed for gesture recognition tasks. By integrating local sensing into the globally focused transformer, we improve its capacity to capture both global and local features in dynamic gesture spectrograms. The experimental results using the dataset we constructed show that the proposed LPVT network achieved a gesture recognition accuracy of 92.2%, which exceeds the performance of other networks.

Vertical Profiles of Aerosol Optical Properties (VIS/NIR) over Wetland Environment: POLIMOS-2018 Field Campaign

This study aims to present the benefits of unmanned aircraft systems (UAS) in atmospheric aerosol research, specifically to obtain information on the vertical variability of aerosol single-scattering properties in the lower troposphere. The results discussed in this paper were obtained during the Polish Radar and Lidar Mobile Observation System (POLIMOS) field campaign in 2018 at a wetland and rural site located in the Rzecin (Poland). UAS was equipped with miniaturised devices (low-cost aerosol optical counter, aethalometer AE-51, RS41 radiosonde) to measure aerosol properties (scattering and absorption coefficient) and air thermodynamic parameters. Typical UAS vertical profiles were conducted up to approximately 1000 m agl. During nighttime, UAS measurements show a very shallow inversion surface layer up to about 100–200 m agl, with significant enhancement of aerosol scattering and absorption coefficient. In this case, the Pearson correlation coefficient between aerosol single-scattering properties measured by ground-based equipment and UAS devices significantly decreases with altitude. In such conditions, aerosol properties at 200 m agl are independent of the ground-based observation. On the contrary, the ground observations are better correlated with UAS measurements at higher altitudes during daytime and under well-mixed conditions. During long-range transport of biomass burning from fire in North America, the aerosol absorption coefficient increases with altitude, probably due to entrainment of such particles into the PBL.

Temporal Associations Between Polarimetric Updraft Proxies and Signatures of Inflow and Hail in Supercells

Recurring polarimetric radar signatures in supercells include deep and persistent differential reflectivity (ZDR) columns, hail inferred in low-level scans, and the ZDR arc signature. Prior investigations of supercell polarimetric signatures reveal positive correlations between the ZDR column depth and cross-sectional area and quantitative characteristics of the radar reflectivity field. This study expands upon prior work by examining temporal associations between supercell polarimetric radar signatures, incorporating a dataset of relatively discrete, right-moving supercells from the continental United States observed by the Weather Surveillance Radar 1988-Doppler (WSR-88D) network. Cross-correlation coefficients were calculated between the ZDR column area and depth and the base-scan hail area, ZDR arc area, and mean ZDR arc value. These correlation values were computed with a positive and negative lag time of up to 45 min. Results of the lag correlation analysis are consistent with prior observations indicative of storm cycling, including temporal associations between ZDR columns and inferred hail signatures/ZDR arcs in both tornadic and nontornadic supercells, but were most pronounced in tornadic storms.

Study on ground-penetrating radar wave field characteristics for earth dam disease considering the medium randomness

Ground-Penetrating Radar (GPR) has been widely used for non-destructive testing of earth dam disease. However, the forward simulation of GPR for earth dam disease often employs layered homogeneous models, neglecting the influence of medium randomness on its wave field characteristics. Therefore, considering the randomness of the medium, a geoelectrical model for earth dam disease is established, which is based on the mixed-type autocorrelation function and the finite element time-domain method. The influence of random medium model parameters on the single-channel wave of GPR is analyzed. The electromagnetic wave propagation characteristics under different medium models are explored. The forward simulation of GPR for earth dam disease such as panel voiding, concentrated seepage, and loosening are performed. The differences in propagation characteristics for earth dam disease between uniform medium model and random medium model are compared. Compared to the calculation results of the uniform medium model, the propagation speed and amplitude of electromagnetic waves in the random medium model changes, and a number of diffraction waves are present. When performing forward simulation of GPR for earth dam disease, considering medium randomness can deepen the understanding of the GPR section view and help improve the accuracy of image interpretation.

Evidence of palaeoenvironmental and climatic changes from the interpreted radar wave pictures of near surface sediments around the River Nile, Assiut, Egypt

Different palaeoenvironmental features that pose natural geological, environmental, and engineering hazards to human operations occur frequently around the Nile Valley. Moreover, where these features were initially created, their relevance focuses on how the urban communities responded to the processes. So, a ground penetrating radar (GPR) field survey was carried out on different paleoenvironments of Pre-Quaternary and Quaternary sediment around Assiut. Deep and critical analyses of georadar facies were made to obtain clear images of these features with unprecedented resolution. The main objective of this study is to find some reasonable geological interpretations for these features. From this study, it is possible to identify and differentiate these features originating from different geological environments and climatological conditions in arid regions such as those around Assiut. In addition, the study serves as guidelines for environmental management and climatic changes for enhancing knowledge of urban development. Also, the study demonstrates how georadar can be used to create precise images of intricate shallow subsurface anatomy with possible palaeoenvironmental and palaeoclimatic indicators.

Efficient Training Data Acquisition Technique for Deep Learning Networks in Radar Applications

In the field of radar, deep learning techniques have shown considerably superior performance over traditional classifiers in detecting and classifying targets. However, acquiring sufficient training data for deep learning applications is often challenging and time consuming. In this study, we propose a technique for acquiring training data efficiently using a combination of synthesized data and measured background data. We utilized graphics processing unit (GPU)-based physical optics methods to obtain the backscattered field of moving targets. We then generated a virtual dataset by mixing the synthesized target signal with the background signal real data. Subsequently, we trained a convolutional neural network using the virtual dataset to identify three different classes—Bird, Drone, and Background—from a range-Doppler map. When tested using the measurement data, the trained model achieved an accuracy of over 90%, demonstrating the effectiveness of the proposed method in acquiring training data for radar-based deep learning applications.

Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters

Ground penetrating radar is a high-resolution, efficient, non-destructive geophysical detection method. It is widely used in various application scenarios such as tunnel geological prediction and road maintenance. Ground penetrating radar data contains a variety of valid signals as well as noise. The diffracted waves of ground penetrating radar contain high-resolution small target imaging information. A critical challenge in GPR applications is how to extract diffracted waves from the wave fields. We provide a strategy to achieve this goal by applying the masking filters. Considering the complexity of the ground penetrating radar wave field and the weak energy of the diffracted waves, the median filter is first employed to suppress the linear reflections and then the f-k filter and filter are implemented to further increase the proportion of diffractions in the wave fields. Three numerical experiments are employed to test the diffraction-separation method.

Trackable Electronic Deception Enabled by Space‐Time Coding Metasurface

AbstractSpace‐time coding metasurfaces (STCMs) have gained a great deal of achievements in the fields of radar and communication, but they have rarely been explored in the field of electronic jamming. The existing researches use time‐varying surface or phase‐switched screens to realize electronic deceptions, but the deceptions are completely passive and are limited in the time‐frequency domain. Here, a mechanism of STCM‐based deceptions is presented in the space and the time‐frequency domains, and precise designs of the STCM‐based deceptions are achieved by performing shifting operations on the space‐time coding sequences of the STCM. Moreover, STCM‐based DOA (direction‐of‐arrival) estimation is integrated with the deception procedure to achieve trackable electronic deception which cannot be realized by completely passive electronic jamming. A prototype system of the STCM‐based deception is built to verify the deception performance, and the experimental results agree well with the numerical simulations. This work extends the research and the applications of the STCMs, hence showing great scientific and engineering significance.

Full‐angle beam scanning leaky‐wave antenna array based on spoof surface plasmon polaritons

AbstractA design scheme of high‐gain and full‐angle frequency beam scanning leaky wave antenna (LWA) and array is proposed based on spoof surface plasmon polaritons (SSPPs) slow‐wave transmission line (TL) for radar field applications. A row of complementary split ring resonators is periodically etched near the SSPPs TL, which can transform the fundamental mode of SSPPs TL to the fast‐wave region and radiate electromagnetic waves, realising the full‐angle frequency beam scanning performance. A 1‐to‐2 microwave power divider is designed to feed the LWA array and realised good impedance matching covers 5.8–9.4 GHz bandwidth. Simulation and experimental results indicate that the designed LWA array can realise full‐angle beam scanning range of 180° (−90° to 90°) with a scanning rate of 3.83°/% performance. The peak gain values of the designed LWA element and array are 11.4dBi and 14.6 dBi, respectively, and the radiation efficiency of LWA array is maintained more than 80% within the operation frequency band.

Coastal Sea Ice Concentration Derived from Marine Radar Images: A Case Study from Utqiaġvik, Alaska

We apply the Canny edge algorithm to imagery from the Utqiaġvik coastal sea ice radar system (CSIRS) to identify regions of open water and sea ice and quantify ice concentration. The radar-derived sea ice concentration (SIC) is compared against the (closest to the radar field of view) 25 km resolution NSIDC Climate Data Record (CDR) and the 1 km merged MODIS-AMSR2 sea ice concentrations within the ∼11 km field of view for the year 2022–2023, when improved image contrast was first implemented. The algorithm was first optimized using sea ice concentration from 14 different images and 10 ice analysts (140 analyses in total) covering a range of ice conditions with landfast ice, drifting ice, and open water. The algorithm is also validated quantitatively against high-resolution MODIS-Terra in the visible range. Results show a correlation coefficient and mean bias error between the optimized algorithm, the CDR and MODIS-AMSR2 daily SIC of 0.18 and 0.54, and ∼−1.0 and 0.7%, respectively, with an averaged inter-analyst error of ±3%. In general, the CDR captures the melt period correctly and overestimates the SIC during the winter and freeze-up period, while the merged MODIS-AMSR2 better captures the punctual break-out events in winter, including those during the freeze-up events (reduction in SIC). Remnant issues with the detection algorithm include the false detection of sea ice in the presence of fog or precipitation (up to 20%), quantified from the summer reconstruction with known open water conditions. The proposed technique allows for the derivation of the SIC from CSIRS data at spatial and temporal scales that coincide with those at which coastal communities members interact with sea ice. Moreover, by measuring the SIC in nearshore waters adjacent to the shoreline, we can quantify the effect of land contamination that detracts from the usefulness of satellite-derived SIC for coastal communities.

Freshly Developed Low‐Latitude Postmidnight‐To‐Dawn F‐Region Ionospheric Irregularities Over China on 13 November 2015

AbstractIn this study, the evolutional features and underlying driving mechanisms of the postmidnight‐to‐dawn equatorial plasma bubble (EPB) irregularities during the weak geomagnetic activity period on 13 November 2015 were investigated based on the multiple satellite and ground‐based observations. By using the coherent scatter radar operating at very high frequency at Fuke (19.5°N, 109.1°E, dip latitude 14.4°N), China, it was found that the freshly developed field‐aligned irregularities (FAIs) occurred within the radar's field of view around ∼04:37 LT and sustained for more than 40 min. The remarkable EPB‐related density and total electron content (TEC) depletions measured by the satellite and GNSS receivers were also observed, which indicates the persistence of EPB irregularities until ∼06 LT. The significant elevation of bottomside F‐layer's virtual height obtained by the Digisonde at Fuke as well as the upward vertical F‐layer plasma drifts derived from a nearby Digisonde at Sanya (18.4°N, 109.6°E, dip latitude 13.1°N) both imply the existence of strong eastward perturbation electric fields after local midnight. These findings suggest that the collective effects of eastward overshielding penetration electric field (PEF) resulted from the substorm onset and rapid northward turning of the interplanetary magnetic field (IMF) Bz, surpassed the role of westward undershielding prompt penetration electric field (PPEF) induced by the southward turning of IMF Bz. Thus, the former predominated in modulating the equatorial/low‐latitude zonal electric fields and raised the F‐layer considerably, which consequently boosted the growth of R‐T instability and created the favorable conditions for the postmidnight‐to‐dawn EPBs development.

RF technology in wireless communications:From transceiver architecture to subsystem specifications

Radiofrequency (RF) technology is essential to wireless communication.The demand for RF technology research is growing as mobile, satellite, radar, and other fields advance. In recent years, the development of 5G and 6G technologies has raised the bar for in-depth RF technology research, requiring greater frequency and data transmission efficiency, among other things. In addition to providing a brief overview of the transceiver's components, the signal chain, and an introduction to the major RF technologies, this paper will concentrate on the architecture of RF transceivers in RF systems and the specification of sub-systems. It will also include references for the RF sub-system specifications and integration techniques. The comprehensive study of communication technology will benefit greatly from an in-depth grasp of the transceiver's capabilities. Lastly, an overview of the layout and features of RF transceivers is provided, along with a prediction of the future application-focused path of RF technology.

Standardization of Dual-Doppler Radar–Derived Wind Fields during a Hurricane Landfall

Abstract A new methodology for standardizing radar-derived elevated dual-Doppler (DD)-synthesized wind maps to the near surface is presented, leveraging the spatial variability found within the horizontal wind speed fields. The methodology is applied to a dataset collected by Texas Tech University (TTU) using two TTUKa-band mobile radar systems during the landfall of Hurricane Delta (2020) in coastal Louisiana. Relevant portions of the DD wind fields are extracted from multiple heights between 100 and 400 m above ground level, combined into 10-min segments and standardized to a reference height of 10 m and an open exposure roughness length of 0.03 m. Extractions from these standardized wind fields are compared and validated against the standardized wind measurements from a micronet of seven TTU StickNet platforms providing “ground truth” within the DD analysis domain. The validation efforts confirm the developed DD wind field standardization methodology yields robust results with correlation coefficients greater than 0.88 and mean biases less than 1%. The results of this study provide a new means for incorporating elevated DD radar data into new and existing surface wind field analysis systems geared toward generating a wind field of record during a hurricane landfall. Significance Statement This work presents a new methodology for using radar-generated wind fields during a hurricane landfall to support the construction of a surface wind field analysis. Because radar-based wind measurements are inherently elevated above the surface and because the wind conditions well above the ground do not directly translate to the wind conditions experienced at the ground, a method for standardizing the elevated radar wind fields to the surface provides tremendous value to generating a spatially continuous wind field of record during a hurricane landfall event to better inform event response and recovery efforts. In addition, the need for detailed wind fields of record from landfalling hurricanes that approach structural design limits is critical as a single design-level storm can alter building code return period analysis. Detailed wind fields for these high-impact events can directly inform associated updates in building codes ultimately contributing to a more resilient built environment.

Study on the optimization process and application of FIR digital filter

As one of the components of digital signal processing technology, the FIR digital filter has been widely used in real life and played an increasingly important role due to its advantages of system stability and ease of linear phase. This paper will summarize and analyze the research results of some past scientific research teams on FIR digital filters, and show the optimization process of this technology and the application examples in real life. This paper focuses on the optimization process of noise reduction performance, delay and size, and energy consumption optimization of FIR digital filters. This study summarizes three examples of its applications in medical, audio processing, and radar. In the medical field, the processing of electrocardiogram (ECG) signals, the audio processing fields are the frequency shaping, noise removal, and signal enhancement of audio signals, and the precise filtering and processing of received signals in the radar field. At the end of this paper, the FIR digital filter has an irreplaceable role in all fields in the world and gradually develops in the direction of miniaturization and low power consumption in the future.

Calibrating Car-Following Models Using SUMO-in-the-Loop and Vehicle Trajectories From Roadside Radar

This paper presents an innovative calibration method for car-following (CF) models in the Simulation of Urban MObility (SUMO) using real-world trajectory data from a 1.5 km signalized urban corridor, captured by roadside radars. By applying a sophisticated track-level association and fusion methodology, the study extends trajectory analysis beyond individual radar fields of view. The enhanced data is then utilized to refine the Krauss, IDM, and W99 CF models within SUMO, addressing the literature gap by integrating SUMO into the calibration loop, thereby accommodating the simulator's integration scheme and any model adaptations. The research identifies that default SUMO models tend to exhibit shorter time headways compared to real-world data, with calibration effectively reducing this discrepancy. Moreover, the W99 model, despite its unrealistic acceleration profiles when calibrated without considering acceleration, most accurately captures the higher-end energy consumption distribution. Conversely, the IDM model, with its default parameters, provides the closest approximation to observed acceleration behaviors, highlighting the nuanced performance of CF models in traffic simulation and their implications for energy consumption estimation. Detailed results of optimized parameters for each CF model are provided in appendix in addition to distribution information that may be useful for other modelers to use directly or other datasets to be compared in the future (including expansion of the work to include vehicle classification).

High-Accuracy Phase Frequency Detection Technology Based on BDS Time and Frequency Signals.

For the time and frequency signals of Beidou satellites, a high-accuracy phase frequency detection technology based on phase group synchronization is proposed. Using the Beidou receiver and satellite signals as the frequency standard and the measured signals, respectively. The Beidou receiver and the satellite signals are sent to the phase coincidence detector of the different frequencies to generate a phase coincidence point pulse, which is sent to the different frequency phase detector as a control signal to generate the phase differences between the Beidou receiver and satellite signals, and then complete the high-accuracy phase synchronization between the Beidou receiver and satellite signals. Experimental results show that when the delay resolution reaches ps level, the phase synchronization accuracy of the system can reach 10 ps, which has the characteristics of small phase noise, low development cost, simple circuit structure, and high synchronization accuracy compared with the traditional phase synchronization technologies. Therefore, it would be widely used in satellite positioning, astrometry, precision navigation, aerospace, satellite launch, power transmission, communications, radar, and other high-tech fields.

A quest for precipitation attractors in weather radar archives

Abstract. Archives of composite weather radar images represent an invaluable resource to study the predictability of precipitation. In this paper, we compare two distinct approaches to construct empirical low-dimensional attractors from radar precipitation fields. In the first approach, the phase space variables of the attractor are defined using the domain-scale statistics of precipitation fields, such as the mean precipitation, fraction of rain, and spatial and temporal correlations. The second type of attractor considers the spatial distribution of precipitation and is built by principal component analysis (PCA). For both attractors, we investigate the density of trajectories in phase space, growth of errors from analogue states, and fractal properties. To represent different scales and climatic and orographic conditions, the analyses are done using multi-year radar archives over the continental United States (≈4000×4000 km2, 21 years) and the Swiss Alpine region (≈500×500 km2, 6 years).

Preparation of Fibrous Three-Dimensional Porous Materials and Their Research Progress in the Field of Stealth Protection.

Intelligent and diversified development of modern detection technology greatly affects the battlefield survivability of military targets, especially infrared, acoustic wave, and radar detection expose targets by capturing their unavoidable infrared radiation, acoustic wave, and electromagnetic wave information, greatly affecting their battlefield survival and penetration capabilities. Therefore, there is an urgent need to develop stealth-protective materials that can suppress infrared radiation, reduce acoustic characteristics, and weaken electromagnetic signals. Fibrous three-dimensional porous materials, with their high porosity, excellent structural adjustability, and superior mechanical properties, possess strong potential for development in the field of stealth protection. This article introduced and reviewed the characteristics and development process of fibrous three-dimensional porous materials at both the micrometer and nanometer scales. Then, the process and characteristics of preparing fibrous three-dimensional porous materials through vacuum forming, gel solidification, freeze-casting, and impregnation stacking methods were analyzed and discussed. Meanwhile, their current application status in infrared, acoustic wave, and radar stealth fields was summarized and their existing problems and development trends in these areas from the perspectives of preparation processes and applicability were analyzed. Finally, several prospects for the current challenges faced by fibrous three-dimensional porous materials were proposed as follows: functionally modifying fibers to enhance their applicability through self-cross-linking; establishing theoretical models for the transmission of thermal energy, acoustic waves, and electromagnetic waves within fibrous porous materials; constructing fibrous porous materials resistant to impact, shear, and fracture to meet the needs of practical applications; developing multifunctional stealth fibrous porous materials to confer full-spectrum broadband stealth capability; and exploring the relationship between material size and mechanical properties as a basis for preparing large-scale samples that meet the application's requirement. This review is very timely and aims to focus researchers' attention on the importance and research progress of fibrous porous materials in the field of stealth protection, so as to solve the problems and challenges of fibrous porous materials in the field of stealth protection and to promote the further innovation of fibrous porous materials in terms of structure and function.