The IEEE Strategic
Electromagnetic Systems
Conclave 2026

Recent trends in SAR, RCS prediction, stealth, and modern sensing reflect a shift toward highly adaptive, data-driven, and integrated electromagnetic systems. Advanced SAR platforms now leverage AI for real-time image processing and target recognition, while compact deployments on UAVs and small satellites enable persistent, high-resolution surveillance. In parallel, RCS prediction has been enhanced through hybrid computational methods and machine learning models that allow faster and more accurate analysis across wide frequency bands and aspect angles. Stealth technologies are evolving beyond conventional shaping and radar-absorbing materials to include metamaterials, multispectral signature reduction, and even active or adaptive techniques. At the same time, modern sensing is moving toward multi-static, networked, and passive systems, often fused with edge computing for rapid decision-making. Together, these developments highlight an ongoing interplay between detection and concealment, driven by advances in computation, materials, and intelligent system design.

Advanced RF and antenna systems are evolving toward highly integrated, adaptive, and high-performance architectures that support modern communication, radar, and electronic warfare applications. Innovations in phased arrays, MIMO systems, and beamforming techniques enable dynamic control of radiation patterns, improved spectral efficiency, and enhanced resilience in contested environments. Advances in materials and fabrication, including metamaterials and additive manufacturing, are enabling compact, lightweight, and multi-band antenna designs. Additionally, the integration of RF subsystems with digital processing and AI-driven optimization is enhancing system efficiency, adaptability, and real-time performance across a wide range of operational scenarios.

Digital and simulation-driven electromagnetic (EM) design is transforming the development of RF and sensing systems by enabling faster, more accurate, and cost-effective design cycles. Advanced computational tools, including full-wave solvers and hybrid modeling techniques, allow engineers to simulate complex electromagnetic interactions across wide frequency ranges and realistic environments. The integration of digital twins and AI-driven optimization further enhances design precision by enabling rapid iteration, performance prediction, and system-level validation before physical prototyping. This approach not only reduces development time and cost but also supports the creation of highly optimized, adaptive, and reliable EM systems for modern applications.