A novel broadband circular-polarized array antenna with ultra-wideband low radar cross section (RCS) is proposed. The array is made up of 2 × 2 identically circular-polarized sub-arrays in a chessboard configuration. Furthermore, each sub-array consists of 2 × 2 tightly coupled metasurfacebased elements with linear polarization. For radiation, each element is excited and fed with 90° phase shift between adjacent ones to perform broadband circular-polarized operation. For scattering, destructive phase difference is created in an ultra-wide band for orthogonally polarized incidence due to the anisotropic structure. Thus, a considerable ultra-wideband RCS reduction involving in-band and out-of-band is achieved based on energy cancellation. By this means, broadband circular-polarized radiation and ultra-wideband low RCS performance can be achieved in a synthesized design process. The prototype is fabricated and measured. A good agreement between measured and simulated results verifies the validity of our design method.

In this paper, we propose a coding electromagnetic metasurface (EMMS) with integrated broadband tunable radiation and low-scattering performance. Anisotropic elements demonstrating opposite phases under x- and y-polarized incidence are investigated and coded as “0” and “1” basic elements. These elements are then arranged in an optimized layout using a simulated annealing algorithm to perform the EMMS. By this means, diffusion scattering is realized in a broadband. Meanwhile, when “0” and “1” are fed properly, the coding EMMS displays wideband linearly or circularly polarized radiation with symmetric profiles. Simulated and experimental results verify that our method offers a simple and ingenious way to integrate broadband radiation and low scattering into one single-coding EMMS.

Synthetic Aperture Radar (SAR) image target detection is of great significance in civil surveillance and military reconnaissance. However, there are few publicly released SAR image datasets of typical non-cooperative targets. Aiming to solve this problem, a fast facet-based SAR imaging model is proposed to simulate the SAR images of non-cooperative aircraft targets under different conditions. Combining the iterative physical optics and the Kirchhoff approximation, the scattering coefficient of each facet on the target and rough surface can be obtained. Then, the radar echo signal of an aircraft target above a rough surface environment can be generated, and the SAR images can be simulated under different conditions. Finally, through the simulation experiments, a dataset of typical non-cooperative targets can be established. Combining the YOLOv5 network with the convolutional block attention module (CBAM) and another detection head, a SAR image target detection model based on the established dataset is realized. Compared with other YOLO series detectors, the simulation results show a significant improvement in precision. Moreover, the automatic target recognition system presented in this paper can provide a reference for the detection and recognition of non-cooperative aircraft targets and has great practical application in situational awareness of battlefield conditions.

A reliable approach based on a two-scale facet-based model and a wave-number spectrum balance equation is presented to analyze the influences from internal waves on electromagnetic scattering from a particular electrically large sea surface. It could be applied to synthetic aperture radar imagery simulation and calculating the scattering coefficients of sea surface with foam, oil film, and ship wake because local scattering coefficients are available. The facet-based model is derived from the Fucks' first-order small perturbation method function, and then, we give the formula of scattering from arbitrary slope facet taking the two-scale model into consideration. The propagation model of internal waves is established by the Korteweg-de Vries equation, and the mechanism of modulation from internal waves to sea surface spectrum is elucidated on the basis of wave-number spectrum balance equation. Moreover, several examples and theoretical analysis are carried out to investigate the impact of internal waves on scattering characteristics under different parameters. Advisable radar parameters to observe internal waves are suggested based on the results of simulations.

An efficient hybrid SIE-KA-FMM method is presented to analyze the electromagnetic scattering from combined conducting and dielectric objects above the rough surface. In this approach, the induced electric current on the rough surface is obtained by the Kirchhoff approximation (KA). The single integral equation (SIE) method is utilized to efficiently compute scattering from the composite target with markedly reducing the numbers of unknowns compared with the conventional coupled integral equation method. The fast multi-pole method (FMM) is incorporated for faster operation and less memory requirement. Several examples verify the validation of the hybrid SIE-KA-FMM method. The composite scattering characteristics of diversiform targets above the rough surface are obtained. Moreover, the numerical results with the different permittivity of dielectric part, polarization mode, working frequency, root mean square (RMS) and correlation length of rough surface, incident pitching/azimuth angle, and target height and target category have been analyzed to provide some useful conclusions.

The increasingly congested frequency spectrum necessitates efficient resource allocation in radar-communication coexistence (RCC) networks. This paper proposes a power-saving-based joint beam-target assignment (BTA), communication-user association (CUA), and power allocation strategy to minimize total power consumption while meeting radar tracking accuracy and communication quality requirements. The posterior Cramér-Rao lower bound (PCRLB) and communication data ratio (CDR) are employed to quantify radar estimation performance and communication efficiency, respectively. To address the NP-hard mixed-integer programming problem, we develop a two-stage cyclically iterative expansion optimization method. This method iteratively expands feasible BTA and CUA domains via convex relaxation while solving power allocation through convex optimization, yielding a suboptimal solution with reduced complexity. Simulations demonstrate that the proposed strategy achieves over 17% lower power consumption compared to state-of-the-art benchmarks while ensuring PCRLB and CDR thresholds. In addition, the framework dynamically prioritizes targets and users with optimal channel conditions, enhancing resource utilization efficiency. The results validate the method's superiority in balancing computational efficiency and performance for extensive simulations.