Radar Detection Research Articles

Screen-Printed Metamaterial Absorber Using Fractal Metal Mesh for Optical Transparency and Flexibility

In stealth applications, there is a growing emphasis on the development of radar-absorbing structures that are efficient, flexible, and optically transparent. This study proposes a screen-printed metamaterial absorber (MMA) on polyethylene terephthalate (PET) substrates using indium tin oxide (ITO) as the grounding layer, which achieves both optical transparency and flexibility. These materials and methods enhance the overall flexibility and transparency of MMA. To address the limited transparency caused by the silver nanoparticle ink for the top pattern, a metal mesh was incorporated to reduce the area ratio of the printed patterns, thereby enhancing transparency. By incrementing the fractal order of the structure, we optimized the operating frequency to target the X-band, which is most commonly used in radar detection. The proposed MMA demonstrates remarkable performance, with a measured absorption of 91.99% at 8.85 GHz and an average optical transmittance of 46.70% across the visible light spectrum (450 to 700 nm), indicating its potential for applications in transparent windows or drone stealth.

Scene-aware data augmentation for ship detection in SAR images

ABSTRACT Ship detection in synthetic aperture radar (SAR) images is widely applied in marine monitoring. In recent years, convolutional neural networks (CNNs) have made significant advances in SAR ship detection. However, the scene imbalance problem, i.e. much more offshore scenes than inshore scenes in SAR images, severely hampers the improvement of detection accuracy. In this article, we propose scene-aware data augmentation to address the problem. First, a novel concept, inshore rate, is introduced to estimate the land area percentage of various scenes in SAR images. We can divide image samples into inshore and offshore ones based on the inshore rate without manual category annotations. Second, to augment inshore samples, we synthesize dummy inshore images by cropping the ground truth bounding boxes (GT bboxes) from offshore images and pasting them onto inshore images. This offline data augmentation strategy can address the scene imbalance problem and improve detection accuracy. The experiments conducted on SAR Ship Detection Dataset (SSDD) and Large-Scale SAR Ship Detection Dataset (LS-SSDD) demonstrate the effectiveness of the proposed method in improving detection performance.

Ultralight Three-Layer Gradient-Structured MXene/ Reduced Graphene Oxide Composite Aerogels with Broadband Microwave Absorption and Dynamic Infrared Camouflage.

Infrared and radar detectors posed substantial challenges to weapon equipment and personnel due to their continuous surveillance and reconnaissance capabilities. Traditional single-band stealth devices are insufficient for dual-band detection in both infrared and microwave bands. To overcome this limitation, a gradient-structured MXene/reduced graphene oxide (rGO) composite aerogel (GMXrGA) is fabricated through a two-step bidirectional freeze casting process, followed by freeze-drying and thermal annealing. GMXrGAexhibits a distinct three-layered structure, with each layer playing a crucial role in microwave absorption. This deliberate design amplifies both the efficiency of microwave absorption and the material's effectiveness in dynamic infrared camouflage. GMXrGA displays an ultralow density of 5.2 mg∙cm-3 and demonstrates exceptional resistance to compression, enduring 200 cycles at a maximum strain of 80%. Moreover, it shows superior microwave absorption performance, with a minimum reflection loss (RLmin) of -60.1dB at a broad effective absorption bandwidth (EAB) of 14.1GHz (3.9-18.0GHz). Additionally, the aerogel exhibits low thermal conductivity (≈26 mW∙m-1∙K-1) and displays dynamic infrared camouflage capabilities within the temperature range of 50-120°C, achieving rapid concealment within 30 s. Consequently, they hold great potential for diverse applications, including intelligent buildings, wearable electronics, and weapon equipment.

Audio analysis speeding detection techniques based on metaheuristic-optimized machine learning models

Law enforcement plays an important role in road safety across the world. Speed enforcement merits special attention as the correlation between exceeding speed limits and the risk of fatalities and serious injuries is well-known. Methods based on radar and light detection and ranging techniques have established themselves as effective methods for measuring vehicle speeds in real time on roads. However, the price of instruments used for these measurements limits their widespread applicability. This work explored the potential of coupling artificial intelligence and audio analysis for vehicle speed assessment. The potential of deep neural networks and extreme gradient boosting is explored on a recently proposed real-world vehicle speed dataset. Frequency analysis techniques are also applied to help reduce the computational demands of experimentation. Additionally, a modified optimization algorithm is introduced to help select optimal control parameters and improve the performance of the suggested method. Five experiments were executed to demonstrate the potential for detecting the exact vehicle speed using regression techniques as well as utilizing classifications to detect vehicles breaking the speed limit. The proposed methods demonstrated promising potential when applied to this pressing challenge.

An Advanced Scheme for Radar Clutter Suppression Scheme Based on Blind Source Separation

In cluttered electromagnetic environments, radar is often disturbed by varied clutter, making target detection challenging. Therefore, achieving effective clutter suppression is crucial for radar target detection. However, traditional clutter suppression methods face three key challenges: (1) significant degradation in target signal detection performance when the clutter’s Doppler spectrum completely masks the target signal; (2) heavy reliance on prior knowledge for optimal performance; and (3) inherent signal energy loss during clutter suppression. To address these challenges, we propose a clutter suppression scheme based on blind source separation (BSS). Initially, the scheme utilizes parallel principal skewness analysis (PPSA) to process the echo signals in the range domain, which helps in identifying the position of moving targets. Subsequently, PPSA is applied once more to process the moving targets in the Doppler domain, allowing for the precise determination of their relative velocities. Subsequently, we evaluate the scheme’s performance with simulated and real data, comparing it with traditional clutter suppression methods and other BSS techniques. The results confirm the effectiveness of the scheme in clutter suppression.

Design of a broadband multifunctional switchable absorber/reflector based on active frequency selective surfaces

Metamaterial absorbers are candidates for stealth systems due to their excellent wave modulation capabilities. With the rapid development of radar detection technology, the switching ability of metamaterial absorbers is becoming more demanding. A broadband multifunctional switchable absorber/reflector based on active frequency selective surfaces (AFSS) is presented in this paper. The proposed structure comprises an absorbing layer, a switching layer, and a ground with air spacers sandwiched between each layer. The PIN diodes can realize significant broadband conditioning performance between absorption and reflection functions by switching four operating states: ‘00’, ‘01’, ‘10’, and ‘11’. The bias network of this structure features horizontal and vertical configurations that independently coordinate the two polarization directions. It is worth noting that the bias network of the designed structure is very simple to minimize the impact on the structure. Distributions of surface current, an equivalent circuit model, and structural parameters are analyzed for a better professional insight into the working mechanism of the absorber/reflector. Finally, a prototype is fabricated and measured to verify the simulation.

Development of a Length-Based Cell-State Framework Toward the Re-Creation of Large-Scale Dense Congestion Patterns

This paper presents the results and novel findings of generating a simplified version of the prevailing traffic features that existed during a major evacuation. Leveraging the underlying framework provided by the widely used cell transmission model, the desire is to reconstruct the unique characteristics of large congestion patterns that propagate under dense traffic states, where limited attempts at scaling this base model have occurred. The length-based cell-state framework presented can reproduce large spatiotemporal congestion patterns that exist, specifically from large-scale evacuations. To further simplify, the framework considers traffic state heuristics which are calibrated through oblique cumulative count and occupancy curves. As a result of this preprocessing technique, an artifact was found from the use of the cumulative curves under the lens of Newell’s two-phase traffic flow theory where three unique, separate queued regimes were identified within the fundamental diagrams. The methodology re-created a unique large-scale congestion pattern that existed during a past regional evacuation event, Hurricane Irma, the subject of this paper. To test this methodology, a large-scale congested period was analyzed, both with probe vehicle trajectory data and stationary radar detector data. Results demonstrate that traffic re-creation into state-based contours was able to be verified near a 90% level of confidence even at large spatiotemporal extents.

Ground-penetration radar detection of Root-mass in a Tree Groove in Southwestern Nigeria

In this study, we present the results of a ground-penetrating radar (GPR) survey aimed at imaging the lateral root systems of a section of a tree groove lined by the Tectona Grandis (Teak) species. This was to set the basis for deploying a multi-frequency GPR system for the non-invasive monitoring of rootmass development and evaluation of plant development and health. The survey involved a single GPR Transect with a total length of 60.1 m established along the middle of a line of matured Teak trees. Data was collected at 250 MHz, 500 MHz and 1000 MHz, simultaneously using a wheel-triggered Utsi Trivue system. Data processing involved a dewow, static corrections, gain application and background removal. A root zone consisting of two layers was delineated and a total of 159 hyperbolae were interpreted as roots. The roots were limited to the shallow subsurface, the upper 1.1 m of a potential root zone 1.6 m deep. Imaged roots generally occur in clusters that create much disturbance of the otherwise continuous reflections in the root zone. Often, roots may be laterally offset from the location of tree bases on the Transect. We further identified a potential set of laterally migrating roots in a zone of undisturbed ground outside the main groove indicating the lateral reach of the usually shallow roots of the Teak tree. The results set the basis for further work in root-mass estimation and monitoring tree health within our team.

Joint waveform design and resource allocation strategy for cognitive radar target situation awareness

AbstractTraditional radar systems use fixed patterns and constant electromagnetic wave transmission to illuminate targets, but they often do not effectively use prior information about targets and consume significant radar resources. Cognitive radar has emerged as a way to improve resource efficiency and address these shortcomings. A joint waveform design and resource allocation strategy for cognitive radar that incorporates target situational awareness is proposed. This method integrates the interacting multiple model algorithm and the Unscented Kalman Particle Filter to achieve target situation awareness as prior knowledge. By combining the target attitude and the frequency response function of the target radar cross section at different time points in the prior knowledge, a joint beam control and power allocation strategy is formulated and transformed into an optimization problem. In addition, a cognitive pulse‐to‐pulse frequency agile waveform design method is proposed to support multiple target tracking under complex motion models. Simulation experiments demonstrate the effectiveness of this approach in obtaining accurate target situation information, achieving beam control, and optimizing power allocation. The designed waveforms can enhance radar target detection performance and improve low probability of intercept characteristics by adjusting the pulse repetition interval. This method has significant technical value.

Chaff jamming recognition and suppression based on semi‐realistic dataset and Pre‐Decluttering Dual‐Stage UNet

AbstractCountermeasures for chaff jamming have drawn great attention in the field of radar target detection and tracking. Current approaches for chaff jamming recognition and suppression exhibit limitations in practical effect, generalisation ability, and hybrid jamming handling. To address the above problems, the authors first transform the traditional 1D signal processing problem into a 2D semantic segmentation task and then solve it from the perspective of the dataset construction and algorithm design. For the dataset construction, the authors use both measured and simulated data to synthesise a more realistic labelled dataset (semi‐realistic dataset), which is also with good diversity due to its adjustable chaff interference background. For the algorithm design, the authors propose a Pre‐Decluttering Dual‐Stage UNet (D2UNet) to recognise and suppress chaff jamming in two stages successively, where the former provides prior attention masks for the latter. To further improve the performance of D2UNet, the authors also design a multi‐stage loss function to achieve progressive training. Extensive experimental results demonstrate that D2UNet delivers remarkable recognition accuracy (99.305%) and suppression performance (41.326 dB peak signal‐to‐jamming ratio, 0.9952 structure similarity index measure) on the semi‐realistic dataset. Its practical effect is further verified on measured data.

A New Extended Target Detection Method Based on the Maximum Eigenvalue of the Hermitian Matrix

In the field of radar target detection, the conventional approach is to employ the range profile energy accumulation method for detecting extended targets. However, this method becomes ineffective when dealing with non-stationary and non-uniform radar clutter scenarios, as well as long-distance targets with weak radar cross sections (RCSs). In such cases, the signal-to-noise ratio (SNR) of the target echo is severely degraded, rendering the energy accumulation detection algorithm unreliable. To address this issue, this paper presents a new extended target detection method based on the maximum eigenvalue of the Hermitian matrix. This method utilizes a detection model that incorporates observed data and employs the likelihood ratio test (LRT) theory to derive the maximum eigenvalue detector at low SNR. Specifically, the detector constructs a matrix using a sliding window block with the available data and then computes the maximum eigenvalue of the covariance matrix. Subsequently, the maximum eigenvalue matrix is transformed into a one-dimensional eigenvalue image, enabling extended target detection through analogy with the energy accumulation detection method. Furthermore, this paper analyzes the proposed extended target detection method from both theoretical and experimental perspectives, validating it through field-measured data. The results obtained from the measured data demonstrate that the method effectively enhances the SNR in low SNR conditions, thereby improving target detection performance. Additionally, the method exhibits robustness across different scattering center targets.

Adaptive radar pulse detection design based on difference of box filter

AbstractPrecise radar pulse detection is the premise of electronic support measures. A constant false alarm rate (CFAR) detection algorithm based on difference of box (DOB) filter is proposed to realise low‐complexity and environment‐adaptive radar pulse detection, and the principle behind the proposed algorithm is revealed. Specifically, the DOB filter is adopted to extract the rising edges and falling edges of radar pulses, and the signal variation law of probability density functions (PDFs) during the process of DOB filter are first theoretically analysed. Based on the derived PDFs, dynamic detection threshold and fixed threshold factor for the proposed CFAR algorithm based on DOB filter are deduced to detect the presence of radar pulses. Furthermore, the closed‐form expression of the detection probability is derived. Simulations and on‐board field programmable gate arrays implementation verify the superiority of the proposed CFAR algorithm based on DOB filter. Simulation results show that the proposed algorithm performs well in detecting various types of pulse signals, the detection probability ≥99% on condition that the signal‐to‐noise ratio ≥3 dB and false alarm probability = 10−8. Moreover, the proposed CFAR algorithm based on DOB filter can deal with both singular pulses and pulse on pulse signals.

Strategy of Russian Military Cooperation with the Countries of the Arab Region

The article undertakes an analysis of the prospective domains of Russian military collaboration with Arab countries against the backdrop of geopolitical uncertainties. Despite maintaining its position as the second-largest arms exporter globally, Russia has experienced a proportional decline in its share of the global arms market. Nevertheless, a discernible uptick in the trade volume of conventional weaponry, coupled with cyclical enhancements in the tactical and technical attributes of military assets, reflects positive momentum in this sector. Amid prevailing external constraints and a noticeable scarcity of contemporary Russian weaponry in burgeoning segments of the arms market, Russia necessitates resolute and equitable measures to uphold and fortify collaborative ties with partner nations. Within this context, particular emphasis is placed on Russia's strategic military cooperation with Arab states, given the region's status as a focal point of geopolitical interests for major economies and a primary destination for arms imports.The article scrutinizes Russia's competitive standing in the arms and military equipment markets of the Arab world, acknowledging the region's significance as a pivotal importer of such goods. Employing a multifaceted evaluation encompassing absolute and relative statistical metrics and derived indices, the study assesses the region's role in global arms procurement. Moreover, it offers an appraisal of the existing state and potential avenues for enhancing the efficacy of the Russian-Arab military-technical collaboration framework. The discourse delves into the transformative prospects of this partnership within the framework of networkcentric warfare concepts. Furthermore, the article elucidates the principal risks inherent in military cooperation among nations at present, highlighting concerns regarding the possible manipulation of military-technical cooperation mechanisms to serve as leverage in furthering the geopolitical aspirations of specific stakeholders.In conclusion, the study posits forward-looking trajectories for bolstering bilateral relations, both sectorally and geographically. These include initiatives such as expanding licensing, leasing, offset transactions, and technology transfer initiatives; advocating for fifth-generation fighter aircraft and long-range radar detection and control systems, leveraging Industry 4.0 technologies; and prioritizing the training of foreign specialists.

0511 High Frequency Radar for Non-Contact Detection of Respiratory Signals During Sleep

0511 High Frequency Radar for Non-Contact Detection of Respiratory Signals During Sleep

Long-Term Coherent Integration Algorithm for High-Speed Target Detection.

Long-term coherent integration (CI) can effectively improve the radar detection capability for high-speed targets. However, the range walk (RW) effect caused by high-speed motion significantly degrades the detection performance. To improve detection performance, this study proposes an improved algorithm based on the modified Radon inverse Fourier transform (denoted as IMRIFT). The proposed algorithm uses parameter searching for velocity estimation, designs a compensation function based on the relationship between velocity and distance walk and Doppler ambiguity terms, and performs CI based on the compensated signal. IMRIFT can achieve RW correction, avoid the blind-speed sidelobe (BSSL) effect caused by velocity mismatch, and improve detection performance, while ensuring low computational complexity. In addition, considering the relationship between energy concentration regions and bandwidth in the 2D frequency domain, a fast method based on IMIRFT is proposed, which can balance computational cost and detection capacity. Finally, a series of comparative experiments are conducted to demonstrate the effectiveness of the proposed algorithm and the fast method.

Evolution Law and Grouting Treatment of Water Inrush in Hydraulic Tunnel Approaching Water-Rich Fault: A Case Study

Tunnel construction adjacent to the fault fracture zone is prone to water inrush disasters, which pose a serious threat to the safety of tunnel construction. To provide theoretical support for the early warning and prevention of water inrush disasters of the tunnel adjacent to the water-rich faults, a numerical analysis based on the three-dimensional discrete element method (DEM) was performed to study the evolution of the displacement and seepage fields of the water-resistant rock mass of a tunnel adjacent to a water-rich fault during the water inrush process by taking the Xianglushan tunnel as the research project. With reference to the obtained results, a grouting reinforcement scheme was developed, and its effectiveness was evaluated. The results indicated that as the tunnel face approached the water-rich fault fracture zone, the effect of water pressure gradually became obvious, and the displacement at the face continuously increased. When the tunnel face was excavated to the position 5 m from the fault, the displacement at the center of the face changed suddenly with a sudden increase in water pressure. The water-resistant rock mass ahead of the center of the face was damaged, and a water inrush disaster occurred in the tunnel. Numerical simulation results demonstrated the feasibility of the grouting reinforcement scheme. The assessment based on the borehole acoustic waves, borehole TV, geological radar detection, and convergence monitoring as well as the excavation results confirmed that the water inrush disasters in the 2# adit of Xianglushan tunnel adjacent to the water-rich fault were effectively prevented and controlled, which can provide a reference for the prevention and treatment of the frequent water inrush disasters in underground projects constructed in the water-rich fault area.

OAM vortex wave interaction with phase modulated metasurface

Phase modulated metasurface (PMM) can control the transmission state of electromagnetic (EM) wave through phase modulation scheme on the interface. Orbital angular momentum (OAM) vortex wave is denoted by the helical phase distribution of the wave front. The interaction between OAM vortex wave and PMM is investigated in this paper. The mathematical model is firstly established according to the array theory. Whereafter, two typical PMMs of chessboard metasurface (CBM) and phase gradient metasurface (PGM) are exploited as examples to uncover the scattering characteristics under illumination of OAM vortex wave. For CBM, the phase cancellation scheme is found to be broken when the OAM order l equals to ±2 under both normal incidence and oblique incidence. It reveals that the OAM vortex wave is a promising approach for metasurface stealth target detection. For PGM, the scattered wave still keeps the OAM feature but is deflected to the non-specular direction, which reveals that the generalized Snell’s law is also suitable to OAM vortex wave. The discoveries of this paper may find applications in radar detection fields using OAM vortex wave.

Research on Coal Mine Geological Exploration Based on Borehole Geological Radar

Drilling geological radar has the advantages of high resolution, large detection depth, and high flexibility in the field of underground exploration, which can provide accurate and reliable data support for geological engineering, mineral resource development, and other fields. Based on the advancements in borehole geological radar detection technology, the borehole geological radar has been successfully introduced into a coal mine in Guizhou, and the actual on-site detection application is carried out. The research results show that the roadway and the evasion chamber can be clearly seen in the detection results of the 1901 aircraft transport alley, and there is an area of obvious signal anomaly in the 1808 return lane boring surface detection section. Drilling radar is applied to coal mine underground, the detection results have strong accuracy and reference, and the promotion and application of coal mine underground have broad prospects.

A Fast IAA–Based SR–STAP Method for Airborne Radar

Space–time adaptive processing (STAP) is an effective technology in clutter suppression and moving target detection for airborne radar. When working in the heterogeneous environment, the number of training samples that satisfy independent and identically distributed (IID) conditions is insufficient, making it difficult to ensure the estimation accuracy of the clutter plus noise covariance matrix for traditional STAP methods. Sparse recovery–based STAP (SR–STAP) methods have received widespread attention in the past few years. The accurate estimation of the clutter plus noise covariance matrix can be achieved using only a few training samples. The iterative adaptive approach (IAA) can quickly and accurately estimate the power spectrum, but applying this method directly to the STAP method cannot produce good performance. In this paper, a fast IAA–based SR–STAP method is proposed. Based on the weighted l1 problem, the IAA spectrum is used as a weighted term to obtain a good approximation. In order to obtain an analytical solution, we use the weighted l2 norm to approximate the weighted l1 norm without loss of performance. Compared with the IAA–STAP method, the proposed method is more robust to errors. Moreover, the proposed method has a fast computational speed. The effectiveness of the proposed method is demonstrated by simulations.

Phase Noise Effects on OFDM Chirp Communication Systems: Characteristics and Compensation

Orthogonal frequency-division multiplexing (OFDM) chirp waveforms are an attractive candidate to be a dual-function signal scheme for the joint radar and communication systems. OFDM chirp signals can not only be employed to transmit communication data through classic phase modulation, but also can perform radar detection by applying linear frequency modulation for subcarriers. However, the performance of the OFDM chirp communication system under the phase noise environment still remains uninvestigated. This paper tries to discuss the influence of phase noise on OFDM chirp communication systems and proposes effective phase noise estimation and compensation methods. We find that the phase noise effect on OFDM chirp communication systems consists of a common phase error (CPE) and an inter-carrier interference (ICI). If not compensated, the performance of the dual-function systems can be seriously degraded. In particular, an exact expression for the signal-plus-interference to noise ratio (SINR) for the OFDM chirp communication system is derived and some critical parameters are analyzed to exhibit the phase noise effects on system performance. Moreover, two low-complexity estimation approaches, maximum likelihood (ML) and linear minimum mean square error (LMMSE), as well as two compensation approaches, the de-correlation and cancellation algorithms, are respectively utilized to eliminate the phase noise impairment. Finally, the phase noise effects and the effectiveness of the compensation approach are verified by extensive numerical results.