Search Results (26)

To address the challenge of evaluating a radar cross-section (RCS) for a non-cooperative aircraft with limited aerodynamic shape information, this paper presents a multi-source, data-driven inverse reconstruction method. This approach integrates data fusion techniques to facilitate an initial shape reconstruction, followed by an iterative optimization process that utilizes computational fluid dynamics (CFD) to enhance the shape, accounting for the aerodynamic performance. Additionally, an inverse deduction analysis is effectively employed to ascertain the characteristics of the power system, leading to the design of a double S-curved tail nozzle layout with stealth capabilities. An aerodynamic analysis demonstrates that at Mach 0.6, the lift-to-drag ratio peaks at 27.3 for the attack angle of 4°, after which it declines as the angle increases. At higher angles of attack, complex flow separation occurs and expands with the increasing angle. The electromagnetic simulation results indicate that under vertical polarization, the omnidirectional RCS reaches its peak as the incident angle is deflected downward by 10° and reduces with the growth of the angle, demonstrating angular robustness. Conversely, under horizontal polarization, the RCS is more sensitive to edge-induced rounding. The findings illustrate that this methodology enables accurate shape modeling for non-cooperative targets, thereby providing a fairly solid basis for stealth performance evaluation and the assessment of surprise effectiveness. Full article

Migrating insects and birds are the primary biological targets in the aerial ecosystem. Radar is a powerful tool for monitoring and studying aerial animals. However, accurately identifying insects and birds based on radar observations has remained an unsolved problem. To address this research gap, this paper proposed an intelligent classification method based on a novel multi-scale time–frequency deep feature fusion network (MSTFF-Net). A comprehensive radar dataset of aerial biological targets was established. The analysis revealed that radar cross section (RCS) features are insufficient to support insect and bird classification tasks, as aerial biological targets may be detected in radar sidelobes, leading to uncertainty in RCS values. Additionally, the motion characteristics of insects and birds are complex, with diverse motion patterns observed during limited observation periods. Simple feature extraction and classification algorithms struggle to achieve accurate classification of insects and birds, making aerial biological target classification a challenging task. Based on the analysis of insect and bird features, the designed MSTFF-Net consists of the following three modules. The first module is the amplitude sequence extraction module, which abandons traditional RCS features and instead extracts the dynamic variation features of the echo amplitude. The second module is the time–frequency feature extraction module, which extracts multi-scale time–frequency features to address the complex motion characteristics of biological targets. The third module is the adaptive feature fusion attention module, which captures the correlation between features to adjust feature weights and achieve the fusion of different feature types with varying representations. The reliability of the classification algorithm was finally verified using a manually selected dataset, which includes typical bird, insect, and other unknown targets. The algorithm proposed in this paper achieved a classification accuracy of 94.0% for insect and bird targets. Full article

To study the influence of speed brake deflection on remote sensing grayscale images and the radar cross section (RCS) of aircraft, we present a comprehensive method based on remote sensing modeling and dynamic electromagnetic scattering. The results indicate that grayscale images from ground remote sensing can capture the hierarchical information of various reference objects and water bodies. When the target aircraft enters the observation area, complex ground reference objects may blur the grayscale features of the speed brake. The RCS of the speed brake shows strong dynamic characteristics under the example of the forward azimuth, where the maximum variation can reach 43.433 dBm². When the speed brakes on both sides dynamically deflect, the aircraft’s RCS in the lateral azimuth will fluctuate significantly in the first half of the observation time, and those in the forward and backward azimuths will show clear dynamic characteristics in the second half of the observation time. Low grayscale ground reference and water body boundaries/areas are beneficial for distinguishing the deflection of the deceleration plate. The comprehensive method proposed here is effective for studying remote sensing grayscale images and the dynamic RCS of aircraft under speed brake deflection. Full article

In recent years, synthetic aperture radar (SAR) technology has been increasingly explored for automotive applications. However, automotive SAR images generated via matched filter (MF) often exhibit challenges such as noisy backgrounds, sidelobe artifacts, and limited resolution. Sparse regularization methods have the potential to enhance image quality. Nevertheless, conventional unweighted ${\mathcal{l}}_1$ regularization methods struggle to address cases with radar cross section (RCS) distributed over a wide dynamic range, often resulting in insufficient sidelobe suppression, amplitude distortion, and inconsistent super-resolution performance. In this paper, we propose a novel reweighted regularization method, termed multi-segment-reweighted regularization (MSR), for automotive SAR image restoration. By introducing a novel weighting scheme, MSR localizes the global scattering point enhancement problem to the mainlobe scale, effectively mitigating sidelobe interference. This localization ensures consistent enhancement capability independent of RCS variations. Furthermore, MSR employs multi-segment regularization to constrain amplitude within the mainlobes, preserving the characteristics of the original response. Correspondingly, a new thresholding function, named Thinner Response Undistorted THresholding (TRUTH), is introduced. An iterative algorithm for enhancing automotive SAR images using MSR is also presented. Real data experiments validate the feasibility and effectiveness of the proposed method. Full article

Unmanned aerial vehicles (UAVs) are increasingly significant in modern warfare due to their versatility and capacity to perform high-risk missions without risking human lives. Beyond surveillance and reconnaissance, UAVs with jet propulsion and engagement capabilities are set to play roles similar to conventional jets. In various scenarios, military aircraft, drones, and UAVs face multiple threats while ground radar systems continuously monitor their positions. The interaction between these aerial platforms and radars causes temporal fluctuations in scattered echo power due to changes in aspect angle, impacting radar tracking accuracy. This study utilizes the potential radar cross-section (RCS) dynamics of an aircraft throughout its flight, using ground radar as a reference. Key factors influencing RCS include time, frequency, polarization, incident angle, physical geometry, and surface material, with a focus on the complex scattering geometry of the aircraft. The research evaluates the monostatic RCS case and examines the impact of attitude variations on RCS scintillation. Here, we present dynamic RCS modeling by examining the influence of flight dynamics on the RCS fluctuations of a UAV-sized aircraft. Dynamic RCS modeling is essential in creating a robust framework for operational analysis and developing effective countermeasure strategies, such as advanced active decoys. Especially in the cognitive radar concept, aircraft will desperately need more dynamic and adaptive active decoys. A methodology for calculating target aspect angles is proposed, using the aircraft’s attitude and spherical position relative to the radar system. A realistic 6DoF (6 degrees of freedom) flight data time series generated by a commercial flight simulator is used to derive aircraft-to-radar aspect angles. By estimating aspect angles for a simulated complex flight trajectory, RCS scintillation throughout the flight is characterized. The study highlights the importance of maneuver parameters such as roll and pitch on the RCS measured at the radar by comparing datasets with and without these parameters. Significant differences were found, with a 32.44% difference in RCS data between full maneuver and no roll and pitch changes. Finally, proposed future research directions and insights are discussed. Full article

With the rapid development of terahertz radar technology, the electromagnetic device for terahertz radar cross-section (RCS) reduction is worth investigating. However, the existing research concentrates on the RCS reduction metasurface with fixed performance working in the microwave band. This paper proposes a terahertz dynamic coding metasurface integrated with vanadium dioxide (VO₂) for dual-polarized, dual-band, and wide-angle RCS reduction. The simulation result indicates that by switching the state of the VO₂ between insulator and metal, the metasurface can realize the effective RCS reduction at 0.18 THz to 0.24 THz and 0.21 THz to 0.39 THz under the left-handed and right-handed circularly polarized incident waves. When the polar and azimuth angles of the incident wave vary from 0° to 40° and 0° to 360° respectively, this metasurface can maintain a 10 dB RCS reduction. This work has potential value in the terahertz stealth field. Full article

This paper presents a forward modeling method for the scattering center (SC) model of dynamic ships on time-varying sea surfaces, tailored for remote sensing and target-recognition applications. Grounded in ship hydrodynamics, the methodology delineates ship movements amidst fluctuating waves, harnessing computer graphics to integrate ship–sea geometries across diverse temporal instances. Utilizing the four-path model, the composite scattering effects are segregated into distinct ship and sea contributions, along with their mutual interactions. Augmented by high-frequency electromagnetic principles, the paper quantifies and deduces SC parameters, culminating in a 3-D parameterized SC model for complex maritime targets. Unlike conventional inverse methods, this approach employs a “cause-to-effect” forward strategy, establishing clear links between SCs and local geometries, enhancing the model’s physical clarity. Using the fishing ship as a case, this research compared the normalized similarity index and position-matching rate between the reconstructed synthetic aperture radar (SAR) image and the simulated SAR image. The results indicate that all computed results exceeded 90%. Furthermore, a comparison was conducted between the reconstructed radar cross-sections (RCS) obtained by expanding the model within a large angular range and the simulated results. The root mean square error between the two was less than 3 dB, affirming the accuracy and effectiveness of the proposed model. Additionally, the research examines the variations in SCs during the six-degrees-of-freedom motions, providing a detailed quantitative analysis of their temporal trends in amplitude and position. In summary, this investigation furnishes an efficient and economical framework for rapid radar characterization in dynamic, variable marine environments, fostering advancements in remote sensing and maritime target identification. Full article

To find a trajectory with low radar detection probability for stealth aircraft under the assumption of 2D space, performing a rapid turning maneuver is a useful way to reduce the radar detection probability of an aircraft by changing the azimuth angle rapidly to reduce the time of high radar cross-section (RCS) exposure to radar. However, in real flight, not only does the azimuth angle to the radar change rapidly but the elevation angle also changes rapidly, and the change in the radar cross-section is also significant in this process. Based on this premise, this paper established a trajectory planning method based on the sparse A* algorithm in a 3D complex, dynamic environment, called the 3D sparse A* method, based on a log-normal radar model (the 3D-SASLRM method), which considers the RCS statistical uncertainty and the statistical characteristics of the radar signals. Simulations were performed in both simple and complex scenarios. It was concluded that the established 3D-SASLRM method can significantly reduce the radar detection probability. And the essence of reducing under the assumption of 3D space is also to reduce the time of high radar cross-section exposure to radar. Full article

This paper deals with the practical application of Radar Cross Section (RCS) reduction technology using plasma. Although various plasma application technologies for RCS reduction have been studied, there are still many issues to be addressed for practical implementation. In order to achieve actual application, the discharge should be sustained regardless of the external environment of the aircraft. It is also important to investigate the actual plasma parameters to determine the expected RCS reduction effect. Building upon previous studies that optimized the electrodes for RCS reduction, this study fabricates a Dielectric Barrier Discharge (DBD) source suitable for dynamic environments and verifies the power consumption during one cycle of plasma generation. The obtained results are expected to contribute to the optimization of DBD electrodes for plasma RCS reduction. Full article

To study the electromagnetic scattering of tilt-rotor aircraft during multi-mode continuous flight, a dynamic simulation approach is presented. A time-varying mesh method is established to characterize the dynamic rotation and tilting of tilt-rotor aircraft. Shooting and bouncing rays and the uniform theory of diffraction are used to calculate the multi-mode radar cross-section (RCS). And the scattering mechanisms of tilt-rotor aircraft are investigated by extracting the micro-Doppler and inverse synthetic aperture radar images. The results show that the dynamic RCS of tilt-rotor aircraft in helicopter and airplane mode exhibits obvious periodicity, and the transition mode leads to a strong specular reflection on the rotor’s upper surface, which increases the RCS with a maximum increase of about 36 dB. The maximum micro-Doppler shift has functional relationships with flight time, tilt speed, and wave incident direction. By analyzing the change patterns of maximum shift, the real-time flight state and mode can be identified. There are some significant scattering sources on the body of tilt-rotor aircraft that are distributed in a planar or point-like manner, and the importance of different scattering sources varies in different flight modes. The pre-studies on the key scattering areas can provide effective help for the stealth design of the target. Full article

Unmanned aerial helicopters (UAHs) have been widely used recently for reconnaissance operations and other risky missions. Meanwhile, the threats to UAHs have been becoming more and more serious, mainly from radar and flights. It is essential for a UAH to select a safe flight path, as well as proper flying attitudes, to evade detection operations, and the stealth abilities of the UAH can be helpful for this. In this paper, a stealth–distance dynamic weight Deep Q-Network (SDDW-DQN) algorithm is proposed for path planning in a UAH. Additionally, the dynamic weight is applied in the reward function, which can reflect the priorities of target distance and stealth in different flight states. For the path-planning simulation, the dynamic model of UAHs and the guidance model of flight are put forward, and the stealth model of UAHs, including the radar cross-section (RCS) and the infrared radiation (IR) intensity of UAHs, is established. The simulation results show that the SDDW-DQN algorithm can be helpful in the evasion by UAHs of radar detection and flight operations, and the dynamic weight can contribute to better path-planning results. Full article

Reasonable allocation of space-based radar resources is a crucial aspect of improving the accuracy of space multi-target tracking and enhancing spatial awareness. The conventional resource allocation algorithm fails to exploit the high dynamic radar cross-section (RCS) characteristics, resulting in poor tracking robustness, tracking divergence, or even loss of tracking. However, the RCS of space targets fluctuates considerably in actual tracking scenarios, which cannot be disregarded for space target tracking tasks. To address this issue, we propose an adaptive allocation method that considers the dynamic RCS fluctuation characteristic for space-based radar tracking assignments. The proposed method exploits the predictable orbital information of space target to calculate the real-time observation angle of radar, and then obtains the multi-target dynamic RCS through the target RCS dataset. By combining the obtained RCS sequence, radar power, and bandwidth, an optimal model for radar tracking accuracy is established based on the multi-target posterior Cramér–Rao lower bound (PCRLB) to evaluate the tracking performance. By resolving the aforementioned multivariance optimization problem, we eventually acquire the results of power and bandwidth pre-allocation for tracking multiple space targets. Simulation results validate that, compared with the traditional methods, the proposed joint dynamic RCS power and bandwidth allocation (JRPBA) method can achieve superior tracking accuracy and minimize instances of missed tracking. Full article

Chaff is a passive jammer widely used to disrupt radar or radio-frequency sensors. A mass of chaff fibers dispersed in the air is commonly referred to as a chaff cloud. It is nearly impossible to numerically simulate in real-time the enormous amount of chaff fibers composing the chaff cloud. In this paper, we model the behavior of numerically estimated chaff clouds as probability density functions (PDFs) and apply approximation techniques to estimate the radar cross-section (RCS) of the chaff cloud in real time. To model the aerodynamics of the chaff cloud, we represented the combination of PDFs as functions of time and wind speed. The applied approximation techniques—vector radiative transfer and generalized equivalent conductor method—showed a computation time that cannot be achieved by low-frequency methods such as the method of moments or finite-difference time-domain. Moreover, the dynamic RCS results of the approximation techniques showed a similar trend to those of other studies simulating similar situations. The proposed scheme is effective for real-time chaff cloud simulation, and the modeled dynamics and estimated dynamic RCSs can be a standard baseline for developing new analysis methods for chaff clouds. In the future, the proposed scheme will extend to more chaff fibers and more diverse environmental parameters. Full article

For tilt-rotor aircraft with coaxial rotors (coaxial rotor aircraft), reduction of radar cross section as well as acoustic noise can be essential for stealth design, and the rotation of the coaxial rotors can have an influence on noise and dynamic radar cross section (RCS) characteristics. In this paper, an approach to the prediction of both the sound pressure level (SPL) of noise and the dynamic RCS of coaxial-tilt aircraft is carried out, based on the theories of the FW-H equation, the physics optics method (PO) and the physical theory of diffraction (PTD) method. In order to deal with the rotating parts (mainly including coaxial rotors), a generated rotation matrix (GRM) is raised, aiming at giving a universal formula for the time-domain grid coordinate transformation of all kinds of rotation parts with arbitrary rotation centers and rotation axis directions. Moreover, a compass-scissors model (CSM) reflecting the phase characteristics of coaxial rotors is established, and a method of noise reduction and RCS reduction based on the phase modulation method is put forward in this paper. The simulation results show that with proper CSM parameter combinations, the reduction of noise SPL can reach approximately 3~15 dB and the reduction of dynamic RCS can reach 1.6 dBsm at most. The dynamic RCS and noise prediction and reduction method can be meaningful for the radar-acoustic stealth design of coaxial tilt-rotor aircrafts. Full article

Developing numerical methods to solve dynamic electromagnetic problems has broad application prospects. In computational electromagnetics, traditional numerical methods are commonly used to deal with static electromagnetic problems. However, they can hardly be applied in the modeling of time-varying materials and moving objects. So far, the studies on numerical methods that can efficiently solve dynamic electromagnetic problems are still very limited. In this paper, a numerical method called the time-domain finite integration technique (TDFIT) is extended to tackle this problem via the introduction of time-varying iterative coefficients. In order to validate the effectiveness of the proposed algorithm, three numerical examples are demonstrated, including two microstrip structures with a time-varying medium and a rapidly rotating structure. The numerical results reveal that the time-varying medium can induce a nonlinear spectrum shift, and the radar cross section (RCS) of a rapidly rotating structure is highly dependent on the rotating speed. The proposed algorithm opens a new avenue for the exploration of many intriguing phenomena in fundamental physics, including frequency conversion and magnetless nonreciprocity. Meanwhile, it can also lead to a wide range of promising practical applications, such as active electron devices, space-time metamaterials, and hypersonic vehicles. Full article