Space-time modulated metasurface (STMM)-based direction-of-arrival (DoA) estimation methods has emerged as a prominent research area in recent years, owing to its remarkable flexibility and low-complexity. However, the receiving antenna is typically positioned in the far-field region of the STMM, thereby having potential risks of direct wave interference (DWI). In this paper, we propose a DoA estimation method based on STMM in the code domain to mitigate the effects of DWI. The wideband DWI shares the same center frequency with the incident waves under estimation, leading to frequency spectrum overlap and making conventional frequency-domain methods ineffective. In contrast, through the design of pseudo-random modulation signals, our proposed method effectively suppresses specific types of wideband DWI within the code domain. As a result, the DoA can be accurately estimated using the interference-suppressed spectrum in the code domain. The novelty of the proposed method lies in its unique approach to DoA estimation within the code domain, along with its ability to effectively counter in-band DWI. To validate the proposed DoA estimation method, we design and fabricate a reconfigurable metasurface operating at the X-band. Experimental results show that the DoA estimation error remains below 2∘ even in the presence of a linear frequency modulation (LFM) DWI, demonstrating the effectiveness and accuracy of the proposed method.

This article presents an accurate automatic forward parametric scattering model with bi-directional ray tracing (BRT) and attribute scattering center (ASC) for complex coated structure. The model can accurately reconstruct the radar cross section (RCS) characteristics and the synthetic aperture radar (SAR) image signatures of targets. Compared with conventional unidirectional ray tracing, higher order scattering types can be obtained through the BRT method. An automatic recognition module for frequency-dependent parameters has been developed based on general equations corresponding to different geometric surface shapes, thereby avoiding cumbersome manual intervention. The reconstructed SAR images utilizing the proposed model exhibit high similarity, surpassing 0.83, compared to those from actual measurements or multilevel fast multipole algorithm (MLFMA). The effectiveness and accuracy of the proposed model are validated through these reconstructed results. Finally, the practicality of the proposed model is demonstrated with a couple of examples.

Deceptive jamming against synthetic aperture radar (SAR) is significant in defending against hostile reconnaissance and securing the region. Traditional jamming approaches primarily aim at single-imagery SAR, signal waveform type, multichannel, array, and degree of freedom. Since the video SAR (VideoSAR) system can enhance reconnaissance capability in detection, recognition, and perception in dynamic region of interest (DROI), it is imperative to devote to the relevant jamming discipline. To the best of our knowledge, it is the first time that a novel deceptive jamming perspective against VideoSAR system is proposed with simultaneously single-channel, single-band, and single-pass configurations. Frame-dependent principle of deceptive modulation against VideoSAR is derived from the video polar format algorithm (PFA). To obtain the VideoSAR deceptive jamming templates with diverse scattering features and high fidelity, a nonsubsampled Shearlet transform scattering characterization controlling approach is proposed for depicting the multidimensional intrinsic correlations of electromagnetic (EM) scattering behaviors. Three high-resolution airborne VideoSAR datasets are employed to confirm the effectiveness of the proposed deceptive jamming in anisotropy scenarios.

In this paper, a temporal mesh-free analytical solution by using the first-order small-slope approximation (SSA-1) method (TSSA-MF) is firstly proposed to analyze the scattering characteristics of the dynamic nonlinear sea surface. The choppy wave model (CWM) is employed to perform the 2-D nonlinear waves. The algorithm starts with incorporating the expression of the nonlinear sea surface fluctuation into the scattering amplitude of the traditional SSA. Then, the TSSA-MF is established to characterize the dynamic nonlinear sea surface by averaging the random time-dependent non-Gaussian surface. The normalized radar scattering cross section (NRCS) can be predicted quickly and accurately by the proposed TSSA-MF. And, comparing with the scattering amplitude of traditional SSA in the statistical sense, the proposed TSSA-MF includes the time variable. Therefore, the time auto-correlation function (TACF) and the Doppler spectrum of nonlinear and linear sea surfaces are analyzed. The simulation results show that the double-peak phenomenon of the CWM is not obvious in the crosswind compared to linear sea surfaces. It should be noted that, mesh generation and averaging a large number of samples can be avoided for the proposed TSSA-MF, so that the calculation time is substantially reduced with encouraging accuracy.

Scattering properties of lunar surface rocks are important guides for remote sensing observation of the lunar surface and discrimination of geologic features. Previous studies primarily focused on the scattering effects of surface or partially buried rocks in terms of angle or frequency, with limited research addressing SAR simulation images of rocks on the lunar surface. This study proposes a three-dimensional (3D) scattering model that integrates the vector radiative transfer (VRT) method with lunar surface rock scattering mechanisms while effectively combining topographic data, rock abundance data, and radar parameters. To implement this model, an end-to-end computational framework is developed to process input datasets and apply the 3D scattering model for backscattering coefficient simulation, reducing uncertainties in the input parameters. Several case studies are performed on Mini-RF observational data. Simulation results demonstrate that the proposed approach shows good consistency with radar data, particularly in terms of distribution characteristics and average backscattering coefficient errors, with an error margin of less than 3 dB.

The synthetic aperture radar (SAR) imaging environment, especially with limited samples, poses a serious challenge to automatic target recognition (ATR) in modern electronic reconnaissance systems. To enhance SAR image recognition performance, this study proposes a technique leveraging a diffusion model and scattering information. This method involves SAR image generation and scattering information processing to improve generalization with few-shot samples. First, the number of few-shot SAR samples was augmented using the denoising diffusion probabilistic model (DDPM). Then, the scattering information is extracted to stably calculate SAR image similarity from the scattering mechanism. Finally, the recognition task is effectively accomplished through the optimal integration of the recognition network and scattering similarity. Simulation results demonstrate that the proposed method achieves superior SAR image generation quality and recognition accuracy compared to the existing methods when the available data are extremely limited.

An efficient mixed-potential integral equation formulation is proposed for the analysis of two-dimensional (2-D) periodic dielectric objects above the half-space. The spatial domain half-space Green’s functions are obtained from the corresponding spectral domain Green’s functions via the discrete complex image method (DCIM) combined with the matrix pencil method (MP) technique. Then, the Poisson’s summation formula is used to express the periodic Green’s function via a combined summation of spectral and spatial terms. However, the half-space Green’s function with 2-D periodicity is commonly expressed as spatial and spectral infinite series that leads to bad convergence. In order to effectively calculate the components of dyadic and scalar mixed-potential half-space periodic Green’s functions, a novel acceleration method is proposed. In this work, the modified Ewald method is applied to the spatial series to accelerate periodic Green’s functions convergence. Numerical results are provided to validate the efficiency of the proposed method. Compared with the traditional spatial method, the accelerated algorithm has faster convergent speed.

An electromagnetic (EM) metasurface is a passive device capable of manipulating the reflected signal of a radar in both spatial and frequency domains. This paper presents a novel analytical design of EM scattering center model guided passive synthetic aperture radar (SAR) deception based on diverse frequency time-modulation. The objective of this design is to disguise real target as an intended deceptive target and conceal its original EM characteristics. To achieve this, we first extract the scattering center model of an intended deceptive target and express its SAR image analytically. The SAR image is determined by the number, amplitude and position of scattering center. Subsequently, we derive the SAR image of a metasurface modulated on fast and slow time scales with diverse frequencies, establishing the relation between modulation parameters and the resulting SAR image properties. By comparing and aligning the SAR images between scattering center model and the modulated metasurface with predetermined similarity threshold, we successfully accomplish scattering center model guided SAR deception. The simulated results demonstrate that the SAR image similarities of both scattering center model and modulated metasurface exceed 0.9, indicating the effectiveness of this method as an electronic countermeasure.

A forward parametric modeling method is proposed to establish three-dimensional (3-D) attributed scattering center (ASC) models for dynamic group targets. The main steps include computer-aided design (CAD) model component decomposition, occlusion analysis for group targets, selection of scattering sources, extracting scattering center parameters, and establishing ASC models for dynamic group targets. With the modeling method, the specular reflection scattering centers, multiple reflections scattering centers, and edge scattering centers can be automatically extracted from CAD model accurately. The method establishes the ASC model with 3-D length parameters to analyze the ASC distributions from a general case. To improve the efficiency of the modeling method, an improved octree structures based occlusion analysis method is proposed to reduce the times of occlusion judgments between targets. Based on the 3-D ASC model, an establishment method is proposed to analyze the time-varying scattering features for dynamic group targets. The establishment method analyzes the correlation of ASC parameters in the time domain, and constructs ASC dataset to efficiently establish the time-varying ASC model. Finally, the results of simulation and measurement are analyzed to validate the effectiveness of the proposed method.

Machine learning-based automatic target detection in video synthetic aperture radar (VideoSAR) has great potential for raising the reconnaissance capability in dynamic region of interest (DROI). In this article, a novel systematic perspective, called low-rank plus sparse multiple-term decomposition (LRSMTD) for simultaneously single-channel, single-band, and single-pass (SCSBSP) VideoSAR configuration is proposed to track the ground defocusing targets. To address the target features of circular VideoSAR imaging, we extend the polar format algorithm (PFA) via exploiting a priori knowledge. In accordance with both the revealed imaging and imagery characteristics, we solve the systematic LRSMTD with proximal exchange-based alternating directions method of multipliers (PEADMM), which makes the process interpretable for defocusing target detection. Comprehensive circular SCSBSP airborne VideoSAR experiments reveal the superior detection performance of the systematic LRSMTD and its several subalgorithms with PEADMM, outperforming 11 state-of-the-art algorithms.

提出一种利用嵌入式均匀柱面透镜设计交叉电桥的新方法。与传统交叉电桥设计相比, 该方法在空气填充的基片集成波导交叉腔内引入一个均匀柱面透镜, 将入射波导向指定方向。根据射线追踪法, 引入的均匀柱面透镜可以在不提高加工复杂度和面积的前提下, 有效束缚从输入端传输到输出端的电磁波。详细阐述了该方法的工作机理, 并通过电场分布进一步予以验证。利用空气填充基片集成波导技术, 研制了工作在毫米波频段的二、三、四通道交叉电桥, 验证了所提方法的可行性。同时引入过渡结构, 便于实验测量。研究发现二、三、四通道空气填充基片集成波导交叉电桥仿真带宽分别为33%、14%和10%, 其核心尺寸分别为0.74λ×0.74λ、1.43λ×1.43λ和1.90λ×1.90λ。最后, 为进一步阐述本文方法的优势, 将其与公开文献中的类似方法进行了比较。

A fast and accurate numerical method based on the theory of characteristic mode (TCM) is proposed for analyzing electromagnetic scattering from repetitive multiscale array structures. In order to overcome the low frequency breakdown problem when interacting at short distances between observation and source basis functions, the CMs are extracted from the impedance matrix generated by the augmented electric field integral equation (AEFIE), which is discretized by the method of moments (MoM). Then the CMs of a single unit are used as the global basis functions to reduce the unknowns of the array structures. In addition, the broadband multilevel fast multipole algorithm (MLFMA) based on approximate diagonalization of the Green’s function is implemented to accelerate the matrix-vector multiplications between the impedance matrix and CM vectors. Several numerical examples are given to demonstrate the high efficiency and accuracy of the proposed scheme.