Radar Technology Research Articles

Metal-organic framework confined preparation of hydrophobic nickel/carbon nanofibers for lightweight and enhanced microwave absorption

The use of a metal-organic framework (MOF) confinement strategy to achieve controllable growth and even allocation of magnetic metal nanoparticles (NPs) in carbon nanofibers (CNFs) can significantly improve the microwave absorption performance of absorbers. Herein, we constructed Ni-MOF in the spinning solution and prepared Ni/CNFs with confined structures using electrospinning combined with carbon thermal reduction. The microstructure of Ni/CNFs was regulated by adjusting the amount of organic ligands added. Ni NPs with single domain size and uniform allocation could optimize impedance matching and enhance electromagnetic synergistic effects, which was beneficial for enhancing microwave absorption performance. When the additional amount of organic ligands was 4 wt%, the absorber reached the optimal microwave absorption performance as the filling ratio was only 3 wt%, the minimum reflection loss (RL) reached –24.9 dB at 13.6 GHz when the thickness was 2.0 mm, and the effective bandwidth (EBW) attained 5.22 GHz. In addition, the excellent hydrophobic performance of nanofibers (NFs) endowed them with potential self-cleaning functions. In addition, to verify the practical application value of the prepared samples in radar stealth technology, we used computer simulation technology (CST) to simulate the samples. Therefore, this work provides a new approach for the controllable preparation of novel magnetic metal/carbon fiber-based absorbers, and also provides a model reference for the controllable growth of magnetic metal particles in the carbon thermal reduction reaction process.

Analisis Efek Doppler dan Implementasinya pada Sistem Radar dan Telekomunikasi: Sebuah Kajian Literatur

The Doppler Effect is a physical phenomenon caused by the relative motion between a wave source and an observer, resulting in a shift in the received wave frequency. This study aims to analyze the Doppler Effect and its implementation in radar and telecommunication systems through a literature review. The findings reveal that the Doppler Effect is a fundamental principle in radar technology, enabling accurate detection of speed, distance, and direction of objects. In telecommunications, however, the Doppler Effect poses challenges, such as frequency shifts that may affect signal quality, particularly in mobile networks, satellite communication, and autonomous vehicles. Various compensation techniques, including adaptive coding and frequency tracking, have been developed to address these issues. The study also highlights technological innovations based on the Doppler Effect, including weather radar, Doppler lidar, and 5G communication networks, showcasing their significant potential for future applications.

Combining radio-telemetry and radar measurements to test optimal foraging in an aerial insectivore bird

Optimal foraging theory posits that foragers adjust their movements based on prey abundance to optimize food intake. While extensively studied in terrestrial and marine environments, aerial foraging has remained relatively unexplored due to technological limitations. This study, uniquely combining BirdScan-MR1 radar and the Advanced Tracking and Localization of Animals in Real-Life Systems biotelemetry system, investigates the foraging dynamics of Little Swifts (Apus affinis) in response to insect movements over Israel’s Hula Valley. Insect movement traffic rate (MoTR) substantially varied across days, strongly influencing swift movement. On days with high MoTR, swifts exhibited reduced flight distance, increased colony visit rate, and earlier arrivals at the breeding colony, reflecting a dynamic response to prey availability. However, no significant effects were observed in total foraging duration, flight speed, or daily route length. Notably, as insect abundance increased, inter-individual distances decreased. These findings suggest that Little Swifts optimize their foraging behavior in relation to aerial insect abundance, likely influencing reproductive success and population dynamics. The integration of radar technology and biotelemetry systems provides a unique perspective on the interactions between aerial insectivores and their prey, contributing to a comprehensive understanding of optimal foraging strategies in diverse environments.

Combining radio-telemetry and radar measurements to test optimal foraging in an aerial insectivore bird.

Optimal foraging theory posits that foragers adjust their movements based on prey abundance to optimize food intake. While extensively studied in terrestrial and marine environments, aerial foraging has remained relatively unexplored due to technological limitations. This study, uniquely combining BirdScan-MR1 radar and the Advanced Tracking and Localization of Animals in Real-Life Systems biotelemetry system, investigates the foraging dynamics of Little Swifts (Apus affinis) in response to insect movements over Israel's Hula Valley. Insect movement traffic rate (MoTR) substantially varied across days, strongly influencing swift movement. On days with high MoTR, swifts exhibited reduced flight distance, increased colony visit rate, and earlier arrivals at the breeding colony, reflecting a dynamic response to prey availability. However, no significant effects were observed in total foraging duration, flight speed, or daily route length. Notably, as insect abundance increased, inter-individual distances decreased. These findings suggest that Little Swifts optimize their foraging behavior in relation to aerial insect abundance, likely influencing reproductive success and population dynamics. The integration of radar technology and biotelemetry systems provides a unique perspective on the interactions between aerial insectivores and their prey, contributing to a comprehensive understanding of optimal foraging strategies in diverse environments.

Development and Demonstration of NDT for Evaluating the Curing Effectiveness of Concrete Pavement Construction

Early-age concrete surface moisture evaporation can be a factor during paving of concrete pavement resulting in plastic shrinkage cracking and spalling related delamination. The use of liquid membrane-forming curing compounds is one of the most prevalent methods to protect hydrating concrete surfaces. However, success in the application of curing compounds is not always assured under field conditions; lacking a tool to evaluate the curing effectiveness in terms of the uniformity and the rate of application are main issues. Previous research focused on the measurement of the surface dielectric constant (DC) of concrete as an indicator of the moisture retention capability of a given method of curing; however, the inherent limitations associated with the previous handheld technology prevents the method from being extensively utilized under field conditions. To employ better curing practices and the qualification of the application of different methods of curing, this research considers the use of ground penetrating radar (GPR) technology to measure DC at the surface of a concrete pavement. Analyses of the DC measurements indicated that the GPR system provided a very useful means to rapidly and extensively evaluate the curing effectiveness over a broad extent of a paved surface with great data repeatability; visual observations and statistical analyses validated that the system was able to suggest the uniformity of curing applications and differentiate the effectiveness of various curing applications due to varied rates of application. The research also reinforces the notion that the moisture retention capability of a given method of curing increases with the increase of the rate of application and improvement of curing uniformity.

A method for monitoring three dimensional surface deformation in mining areas combining SBAS-InSAR, GNSS and probability integral method

In the process of mineral resource extraction, monitoring surface deformation is crucial for ensuring the safety of engineering and ground infrastructure. Monitoring complete three-dimensional surface deformation is particularly significant. Traditional synthetic aperture radar (InSAR) technology provides deformation components only along the line of sight (LOS) and often lacks sufficient effective data in vegetation-covered mining areas and mining subsidence centers. To address this, this study proposes a method (SBAS-PIM) that combines SBAS-InSAR with the probabilistic integral method (PIM). This method leverages high-coherence points in mining areas and GNSS data from vegetation-covered regions to invert the parameters required by PIM, thus obtaining three-dimensional surface deformation results. The proposed method allows for the acquisition of three-dimensional deformation data with fewer InSAR points and GNSS data, significantly reducing labor costs and addressing the gap in InSAR monitoring of three-dimensional surface deformation in densely vegetated areas. Additionally, it accounts for the mutual influence of multiple adjacent working faces. Finally, through the application to a mining area in Heze, China, the maximum displacements in the vertical, east–west, and north–south directions were obtained as −2011, −418, and − 281 mm, respectively. The correlation coefficients between the vertical and east–west directions and GNSS data were both greater than or equal to 0.9, indicating that this method can effectively monitor the three-dimensional surface deformation of the mining area.

FMCW-based contactless heart rate monitoring

Heart disease is a significant global health issue. Traditional methods for heart rate monitoring typically require close physical contact, which limits the continuity and convenience of monitoring. To achieve real-time, non-contact heartbeat monitoring, researchers have introduced millimeter-wave radar technology. The technology’s penetration and privacy offer a potential solution for heart condition monitoring. Therefore, this study utilized frequency-modulated continuous wave (FMCW) radar for heart rate monitoring. Firstly, the collected millimeter-wave radar signals were preprocessed to accurately locate the area of cardiac activity in the human body. Secondly, an adaptive variational mode decomposition (A-VMD) algorithm was designed to extract the heartbeat signal, considering signal variations caused by random body movements and respiration and their harmonics, to obtain an accurate heartbeat signal. Finally, the accurate heart rate is obtained by weighted estimation based on the harmonic relationship of the heartbeat signal. The study invited ten subjects to participate in the experiment to verify the effectiveness of this method. The results show that this method can reduce the influence of and random body movements and respiration and harmonics on heart rate monitoring, the average absolute error of heart rate estimation is less than four bpm.

Space-based long term condition monitoring of cold region pavement with PS-InSAR

The durability of cold-climate pavement is affected by ground frost heave and thaw settlement. Field monitoring of pavement elevation changes remain challenging and expansive. This study demonstrates space-based Interferometric Synthetic Aperture Radar (InSAR) technology as a potential way to monitor seasonal pavement elevation change in cold region. Traditional InSAR applications, which were designed for geoscience scales, do not achieve the needed sensitivity or spatial resolution for pavement engineering applications. The testbed used is a cold-region airport located in Qinghai Province, China. The site contains heterogeneous ground conditions in an area of 4km × 6km. Analyses were conducted using 132 ascending and 149 descending C-band InSAR images from the Sentinel-1 satellite. InSAR algorithm based on Persistent scatterers (PS-InSAR) were implemented for data analyses. Time series displacement across five distinct persistent scatterers (PSs) groups at different locations were obtained. From these, three main seasonal vertical ground deformation patterns were identified, each reflecting the diverse subsurface soil characteristics across the sites. The ground elevation changes were decomposed into baseline trend and seasonal changes. The results of seasonal ground deformations allowed to differentiate the ground soils as frost-susceptible and non-frost-susceptible, an important information for geotechnical site investigation. This helps identify areas of pavement subjected to frost heave and thaw weakening. The study demonstrates that potential of space-based InSAR technology to achieve spatial resolution and sensitivity for monitoring the performance of cold region pavement. The results allow to identify areas of pavement vulnerable to cold region climate and climate change.

Polarization Scattering Regions: A Useful Tool for Polarization Characteristic Description

Polarimetric radar systems play a crucial role in enhancing microwave remote sensing and target identification by providing a refined understanding of electromagnetic scattering mechanisms. This study introduces the concept of polarization scattering regions as a novel tool for describing the polarization characteristics across three spectral regions: the polarization Rayleigh region, the polarization resonance region, and the polarization optical region. By using ellipsoidal models, we simulate and analyze scattering across varying electrical sizes, demonstrating how these sizes influence polarization characteristics. The research leverages Cameron decomposition to reveal the distinctive scattering behaviors within each region, illustrating that at higher-frequency bands, scattering approximates spherical symmetry, with minimal impact from the target shape. This classification provides a comprehensive view of polarization-based radar cross-section regions, expanding upon traditional single-polarization radar cross-section regions. The results show that polarization scattering regions are practical tools for interpreting polarimetric radar data across diverse frequency bands. The applications of this research in radar target recognition, weather radar calibration, and radar polarimetry are discussed, highlighting the importance of frequency selection for accurately capturing polarization scattering features. These findings have significant implications for advancing weather radar technology and target recognition techniques, particularly as radar systems move towards higher frequency bands.

A Novel Full‐Band Microwave Absorber Based on Scattering Enhanced Prism‐Honeycomb Nested Structure

AbstractWith advancements in radar detection technology, electromagnetic stealth has garnered significant attention in military applications. Traditional electromagnetic absorbers typically focus on tuning electromagnetic parameters; however, they are often limited by material constraints, resulting in effective absorption only within narrow frequency bands. This work presents a novel prism‐honeycomb nested microwave absorbing structure, inspired by the scattering phenomenon of light waves in a prism, which utilizes an enhanced scattering effect. The varying impedances of electromagnetic waves (EMWs) in different media lead to transmission and reflection that adhere to Snell's law at the interfaces. To optimize the scattering effect, the inner prism is filled with a high transmittance material, while the outer honeycomb structure incorporates a material with high dielectric loss. Consequently, electromagnetic waves experience significant attenuation within the unit. Despite a thickness of only 7 mm, this structure achieves over 90% EMW absorption across a broad frequency range of 1–18 GHz. Additionally, the honeycomb structure exhibits excellent mechanical load‐bearing capacity. The nesting of the prism further enhances support points, resulting in a compressive strength of 16.4 MPa. This innovative design not only facilitates full‐band absorption but also provides high mechanical load‐bearing capabilities, offering valuable insights for applications in electromagnetic stealth and camouflage.

Advanced Scattering Analysis of Targets Under Plane Waves and Electromagnetic Vortex Waves for Stealth Applications

This study investigates the scattering characteristics of typical metallic targets under the influence of electromagnetic vortex waves, with a focus on Radar Cross Section (RCS) and Orbital Angular Momentum Radar Cross Section (ORCS). Using the physical optics approximation, the induced current density on the target surface was calculated, and the backscattered field was derived. The comparative analysis highlights the advantages of electromagnetic vortex waves over plane waves in stealth applications, with an in-depth examination of the impact of different OAM modes on power distribution and flat plate scattering characteristics. The unique properties of electromagnetic vortex waves show promising applications in stealth radar and target detection. Furthermore, the study discusses the potential for using OAM waves in enhancing radar system performance, target identification, and electronic countermeasures. The ability of OAM waves to provide selective detection capabilities and reduce RCS under certain conditions makes them particularly valuable for military stealth applications. The combination of MIMO technology with OAM waves is also explored as a means to further improve detection capabilities and flexibility. The findings suggest that electromagnetic vortex waves have a broad range of applications beyond stealth, including radar sensing, imaging, and rotational Doppler detection, thereby opening new avenues for advanced radar technologies

Research on the problem of landmines and explosive remnants of war worldwide and methods of demining

The study addresses the global issue of landmines, with a particular focus on the challenges in Bosnia and Herzegovina. The research is grounded in precise data and facts from institutions and accredited demining organizations. The study further concentrates on innovative and highly effective detection methods, specifically for areas with challenging topography like Bosnia and Herzegovina, concluding with an innovative application of GPR and LiDAR radar technologies. Additionally, it explores the most effective method for mine removal, and mechanical demining, providing a detailed overview of the operation and characteristics associated with this approach. Conclusively, the study proposes the most efficient solution: a combined system of flails and tillers that alternately complement each other to achieve complete mine clearance.

Vehicle-mounted Millimeter-wave Radar Target Recognition Technology

Vehicle-mounted millimeter-wave radar target tracking technology is a technology that uses millimeter-wave radar equipment to detect and track targets around the vehicle. This technology relies on specific characteristics of radar signals, such as frequency and amplitude, and analyzes the reflected signals from targets to gather information. Through algorithm processing and analysis, it can track the target's position, speed and trajectory. The basic principle of vehicle-mounted millimeter-wave radar target tracking is to use radar equipment to transmit radio frequency signals. When the signal encounters an object, it is reflected back to the radar device, providing information about the target. This article explains this new technology in three parts: the working principle of millimeter-wave radar, various cutting-edge algorithms in the technology, and its application in vehicles. The integration of millimeter-wave radar technology represents a significant advancement in vehicle safety and autonomous driving capabilities. Furthermore, understanding these technological components is crucial for developing more efficient and reliable vehicle detection systems.

Three-Dimensional Deformation Prediction Based on the Improved Segmented Knothe–Dynamic Probabilistic Integral–Interferometric Synthetic Aperture Radar Model

Coal is the main mineral resource, but over-exploitation will cause a series of geological disasters. Interferometric synthetic aperture radar (InSAR) technology provides a superior monitoring method to compensate for the inadequacy of traditional measurements for mine surface deformation monitoring. In this study, the whole process of mining a working face in Huaibei Mining District, Anhui Province, is taken as the object of study. The ALOS PALSAR satellite radar image data and ground measurements were acquired, and the ISK-DPIM-InSAR deformation monitoring model with the dynamic probabilistic integral model (DPIM) was proposed by combining the probabilistic integral method (PIM) and the improved segmented Knothe time function (ISK). The ISK-DPIM-InSAR model constructs the inversion equations of InSAR line-of-sight deformation, north–south and east–west horizontal movement deformation, vertical deformation, inverts the optimal values of the predicted parameters of the workforce through the particle swarm algorithm, and substitutes it into the ISK-DPIM-InSAR model for predicting the three-dimensional dynamic deformation of a mining face. Simulated workface experiments determined the feasibility of the model, and by comparing the level observation results of the working face, it is confirmed that the ISK-DPIM-InSAR model can accurately monitor the three-dimensional deformation of the surface in the mining area.

Smart furniture using radar technology for cardiac health monitoring

The integration of radar technology into smart furniture represents a practical approach to health monitoring, circumventing the concerns regarding user convenience and privacy often encountered by conventional smart home systems. Radar technology’s inherent non-contact methodology, privacy-preserving features, adaptability to diverse environmental conditions, and high precision characteristics collectively establish it a compelling alternative for comprehensive health monitoring within domestic environments. In this paper, we introduce a millimeter (mm)-wave radar system positioned strategically behind a seat, featuring an algorithm capable of identifying unique cardiac waveform patterns for healthy subjects. These patterns are characterized by two peaks followed by a valley in each cycle, which can be correlated to Electrocardiogram (ECG), enabling effective cardiac waveform monitoring. The provided algorithm excels in discerning variations in heart patterns, particularly in individuals with prolonged corrected QT intervals, by minimizing high frequency breathing interference and ensuring accurate pattern recognition. Additionally, this paper addresses the influence of body movements in seated individuals, conducting a comprehensive study on heart rate variability and estimation. Experiment results demonstrate a maximum interbeat intervals (IBI) error of 30 milliseconds and an average relative error of 4.8% in heart rate estimation, showcasing the efficacy of the proposed method utilizing variational mode decomposition and a multi-bin approach.

Identification and Analysis on Surface Deformation in the Urban Area of Nanchang Based on PS-InSAR Method

Interferometric Synthetic Aperture Radar (InSAR) technology has emerged as a vital tool for monitoring surface deformation due to its high accuracy and spatial resolution. With the rapid economic development of Nanchang, extensive infrastructure development and construction activities have significantly altered the urban landscape. Underground excavation and groundwater extraction in the region are potential contributors to surface deformation. This study utilized Sentinel-1 satellite data, acquired between September 2018 and May 2023, and applied the Permanent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to monitor surface deformation in Nanchang’s urban area. The findings revealed that surface deformation rates in the study area range from −10 mm/a to 6 mm/a, with the majority of regions remaining relatively stable. Approximately 99.9% of the monitored points exhibited deformation rates within −5 mm/a to 5 mm/a. However, four significant subsidence zones were identified along the Gan River and its downstream regions, with a maximum subsidence rate reaching 9.7 mm/a. Historical satellite imagery comparisons indicated that certain subsidence areas are potentially associated with construction activities. Further analysis integrating subsidence data, monthly precipitation, and groundwater depth revealed a negative correlation between surface deformation in Region A and rainfall, with subsidence trends aligning with groundwater level fluctuations. However, such a correlation was not evident in the other three regions. Additionally, water level data from the Xingzi Station of Poyang Lake showed that only Region A’s subsidence trend closely corresponds with water level variations. We conducted a detailed analysis of the spatial distribution of soil types in Nanchang and found that the soil types in areas of surface deformation are primarily Semi-hydromorphic Soils and Anthropogenic Soils. These soils exhibit high compressibility, making them prone to compaction and significantly influencing surface deformation. This study concludes that localized surface deformation in Nanchang is primarily driven by urban construction activities and the compaction of artificial fill soils, while precipitation also has an impact in certain areas.

An optimization method for terahertz metamaterial absorber based on MOPSO

Metamaterials can freely control terahertz waves to obtain the desired electromagnetic characteristics by designing the geometry and direction of the unit structure, which is widely used in sensing, communication and stealth technology in radar. The traditional design of terahertz metamaterial absorber usually requires continuous structural adjustment and a large number of simulations to meet the expected requirements. The process is heavily dependent on the experience of researchers, and the physical modeling and simulation solution process is time-consuming and inefficient, which has greatly hindered the development of metamaterial absorbers. Therefore, deep learning has been used to predict the structural parameters or spectra of metamaterial absorbers due to its powerful learning ability. However, when designing a new structure, a large number of training samples need to be reprepared, which is time-consuming and not universal. Particle swarm optimization can quickly converge to the optimal solution through the sharing and cooperation of individual information in the group, without prior preparation. Therefore, this paper proposed a fast design method of terahertz metamaterial absorber based on multi-objective particle swarm optimization algorithm. Taking a new center symmetric absorber structure composed of four L as an example, the structure parameters are optimized to achieve fast automatic design of metamaterial absorber. The multi-objective particle swarm optimization takes the absorptivity and quality factor as independent targets to design the structure parameters of the absorber, realizes the dual-objective optimization of the absorber, and overcomes the shortcoming of the multi-objective conflict that PSO cannot solve. The optimally-designed absorber achieves perfect absorption at 1.613THz with a quality factor of up to 319.72 and a sensing sensitivity of 264.5GHz/RIU when used for refractive index sensing. In addition, the causes of absorption peaks are analyzed in detail using impedance matching, surface current, and electric field distribution. By studying the polarization characteristics of the absorber, it is found that it is not sensitive to polarization, which is more stable in practical application. In summary, the multi-objective particle swarm optimization algorithm can realize the design according to the demand, reduce the experience requirement of researchers in the design of metamaterial absorber, improve the design efficiency and performance, and have great application potential in the design of terahertz functional devices.

Automatic detection of road subsurface distress utilizing ground penetrating radar technology: A state-of-the-art review

Automatic detection of road subsurface distress utilizing ground penetrating radar technology: A state-of-the-art review

Research on methods to enhance the survivability of AWACS with FDA against anti‐ARMs on a battlefield

AbstractThe Airborne Warning and Control System (AWACS) are pivotal assets in aerial operations, necessitating specialised protection measures, and serving as prime targets for enemy anti‐radiation missiles (ARMs). This paper explores approaches to enhance the battlefield survivability of frequency diverse array AWACS (FDA‐AWACS) by incorporating airborne radar technology onto the platform. The study commences by analysing the typical operational methods of anti‐radiation missiles. Following this, a deception model is formulated for the frequency diverse array (FDA) against the passive radar homing head of anti‐radiation missiles utilising the adjacent antenna single‐pulse amplitude‐comparison direction‐finding technique. Expanding on this groundwork, the research further assesses the deceptive impacts of FDA‐AWACS on direction finding cross‐location techniques. Simulation results validate that FDA‐AWACS can effectively counter the threat of anti‐radiation missiles by diminishing their direction‐finding and positioning systems.

Monitoring surface deformation of the Qinghai–Tibet permafrost region using an improved MT-InSAR method based on spatial–temporal constraints

ABSTRACT Monitoring ongoing permafrost degradation on the Qinghai–Tibet Plateau is challenging because of its underground characteristics. Interferometric synthetic aperture radar (InSAR) technology, which can detect large-scale and high-precision surface deformation, has become an effective tool for indirect permafrost monitoring. Traditional InSAR methods usually solve permafrost deformation independently and on a point-by-point basis with high coherence, while existing permafrost deformation models ignore the interannual variation in deformation. This paper proposes an improved multi-temporal InSAR (MT-InSAR) method based on spatial–temporal constraints for monitoring permafrost deformation. The method establishes a segmented permafrost deformation model considering the interannual variation in deformation over time. The spatial similarity constraint is subsequently introduced to establish the relationship between deformations at neighboring points, improving the results of permafrost monitoring. Both simulated and real experiments confirmed the ability of the proposed method to capture interannual variations in permafrost deformation with higher accuracy and point density. A real experiment with Sentinel-1 data revealed significant interannual variations in surface deformation within the Wudaoliang-Tuotuohe permafrost region from 2018–2021, characterized by decreased linear deformation and slight seasonal deformation changes. Compared with the traditional methods and in-situ data, the deformation accuracy and point density can be improved by approximately 15.6% and 19.4%, respectively.