A novel electronically controlled (EC) leaky-wave antenna (LWA) based on Corrugated Substrate Integrated Waveguide (CSIW) with fixed-frequency beam-steerable capability is presented in this letter. This structure is based on a CSIW structure with rectangular ring slots and metallic vias to the ground, which realizes two isolated DC equipotential planes. Each slot of the rectangular ring is loaded with a varactor diode, and thus the series and shunt capacitance are tunable by adjusting the DC bias voltage, which eventually results in beam scanning at a fixed frequency. The proposed antenna is a single-layer structure and has a simplified DC bias network, which merely needs an inductor and a short microstrip line. An electronically controlled beam-steerable CSIW LWA is designed and experimentally validated. It is experimentally demonstrated that the radiation angle ranges from -40.66° to 31.32° as the bias voltage is tuned from 32 V to 7.5 V at 4.5 GHz.

A novel forward method to establish the three-dimensional(3-D) parametric scattering center models is developed to extract scattering centers from the combined target/rough surface models. Both scattering centers from ship including single-order and higher-order scattering contributions, and from the multiple interactions between ship and random rough sea surface, would be described concisely with physically relevant parameters by this proposed method. Due to the statistical nature of the random rough surface for the Monte Carlo simulation, we acquire a large number of realizations for estimations of the amplitude and position parameters to overcome the problem that single realization cannot extract scattering centers effectively. This method is validated through parametric models of the ship in free space and on the sea surface and good agreement has been demonstrated between the constructed and simulated radar characteristics. Further, we analyze the composite target/surface model's physics and feature stability in visually spatial range and direct connections between scattering centers and scattering sources, which would be valuable to future target recognitions and classifications. Finally, we quantitatively calculate and analyze the coupling scattering centers from interactions between ship and the ocean-like surface that provide more abundant contour information of the ISAR image to facilitate contour detections.

This article presents a forward modeling method for the scattering center (SC) model of coated targets on rough ground, tailored for remote sensing and target recognition applications. The methodology initiates with the geometric model and coating impedance parameters of the ground target, employing a forward approach to decompose overall scattering into multiple component-level sources. Integrating high-frequency electromagnetic (EM) theory, quantitative computation, and derivation of SC parameters constructs a parameterized 3-D model for coated targets on rough ground. Illustrated through the example of a T72 tank and considering the effects of coated media and ground coupling, a forward SC model for the tank target on rough ground is developed. The model’s statistical characteristics are meticulously analyzed, and its accuracy is validated using real measurement data from publicly available datasets. The proposed model offers several advantages. First, it directly reflects the local geometry and coated material characteristics of target components, providing detailed information about component shapes and materials. Second, the modeling process meticulously considers and segregates the contributions of the target’s complex coupled SCs with the ground. A statistical analysis demonstrates consistent parameter convergence, aligning with theoretical expectations. Third, this research extends the forward modeling approach to coated targets on rough ground, enabling the model not only for component-level identification but also for rapid target synthetic aperture radar (SAR) echo reconstruction. In conclusion, this cost-effective approach provides a practical means for the rapid estimation and analysis of radar characteristics, target detection and recognition, target remote sensing, and other applications in complex environments.

Machine learning-assisted synthetic aperture radar (SAR) automatic target recognition (ATR) methods have gained widespread attention and application. Among them, the methods based on the convolutional neural network (CNN) have achieved good results under standard operating conditions (SOCs) because the CNN can automatically extract and learn the image feature from the SAR image. Still, they show poor performance under extended operating conditions (EOCs) due to the change of the radar imaging conditions, especially when the depression angle of radar imaging changes a lot. Compared to the image features, the scattering center (SC) can provide a concise and physically relevant description of the target scattering characteristics. To achieve a good recognition performance under both SOC and EOC, we propose an SAR ATR method based on the SC features and graph neural networks with featurewise linear modulation (GNN-FiLM). By quantifying and representing scattering features with the physical parameters of SCs, the SC features are introduced into the training of GNN-FiLM in the form of a graph. The structure features and physical information are extracted and learned by the GNN-FiLM. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) and simulation datasets demonstrate that our method can perform well in recognition experiments of three-class targets. Especially under EOC of large depression variant on the MSTAR dataset, our method can obtain about 91.5% accuracy, which is better than other deep learning-based methods.

This paper proposes a forward method to establish the bistatic attributed scattering center (BASC) model for general complex targets. The BASC models constructed forward are exactly what downstream users expect, being able to accurately and concisely describe the bistatic scattering characteristics of complex targets, while also providing the clarity on physical formation process and carrying detailed target information. We firstly use a spatial ray clustering technique to effectively separate the bistatic scattering sources at component level. Then, we establish the parametric attributed model for bistatic scattering center, based on the quantitative forward analysis and derivation of electromagnetic wave-target interaction process. The 3D position is calculated according to the uniqueness, determinism and the principle of equal optical path. From physical causes and conditions, the distribution length of BASC is given directly. The frequency dependence is rapidly determined by characterizing the distribution of specular points, thereby avoiding the burden of surface fitting for complex shapes. Finally, as the accuracy test of proposed method, the model-predicted responses are shown to agree with the results obtained from validated high-frequency simulations. In addition, the characteristic differences of bistatic scattering centers detected from the multiple receive platforms in different directions are discussed.

An efficient physical optics (PO) calculation method is proposed for the electromagnetic (EM) scattering of electrically large targets coated with magnetized plasma characterized by asymmetric tensor dielectric parameters. The outer surface of the arbitrarily shaped target is discretized into triangular elements. According to the principle of tangent plane approximation and by using the plane wave spectrum expansion method, the scattered field from one triangular element is derived as a double integral in the spectral domain. To obtain the solution in the spatial domain, the saddle point method is used to asymptotically calculate the integral. Then, the equivalent surface currents (ESCs) are constructed by calculating the surface field at the outer surface of the planar model, from which the PO solution is derived by using the Stratton–Chu integral. Moreover, to interpret the field propagation process in the plasma layer quantitatively, the total scattered field of the coated planar model is decomposed into the superposition of different mode field components. It is observed that the scattered fields demonstrate an inherent cross-polarization phenomenon due to the nonreciprocal constitutive relation of the plasma, which is a distinct feature and is different from the general anisotropic medium whose dielectric parameters can be diagonalized. The effectiveness of the proposed method is verified by numerical results. Furthermore, the proposed algorithm consumes less calculation time and memory as compared to commercial full solvers.