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

Distributed electromagnetic sensing has emerged as a powerful approach for inferring three
dimensional 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 three
dimensional 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.