Distributed Electromagnetic Sensing for Local 3D Reconstruction: Geometry, Field Superposition, and Fundamental Limits

Distributed electromagnetic sensing has emerged as a powerful approach for inferring threedimensional structure in environments that are not directly observable. By combining measurements from multiple spatially separated emitters and receivers, such systems aim to reduce geometric ambiguity and improve reconstruction fidelity relative to single-node configurations. Despite growing interest in cooperative and networked sensing architectures, the fundamental physical limits governing what can be reconstructed are often obscured by application-specific assumptions. This paper presents a theoretical analysis of distributed electromagnetic sensing for local threedimensional reconstruction, with emphasis on wavelength-dependent resolution constraints, penetration–detail tradeoffs, and noise-induced uncertainty. A general physical model of electromagnetic propagation and signal–matter interaction is developed to examine how spatial geometry and measurement diversity influence reconstructability. It is shown that distributed geometries enhance inference primarily by introducing spatial diversity, rather than by overcoming fundamental wave-based limitations. The role of quantum-enhanced sensing is also examined, clarifying that quantum techniques can improve measurement precision near noise limits but do not alter the underlying constraints imposed by electromagnetic wave physics and information availability. Overall, this work provides a unified framework for understanding the capabilities and limitations of cooperative electromagnetic sensing systems, offering guidance for realistic interpretation and responsible application in civilian contexts.