Fundamental Limits for Near-Field Sensing -- Part I: Narrow-Band Systems

TL;DR

This paper develops a theoretical framework for near-field sensing with extremely large antenna arrays, deriving bounds on estimation accuracy that account for near-field effects and guiding system design.

Contribution

It introduces a unified narrow-band near-field signal model and derives explicit CRB expressions, revealing how near-field effects influence sensing limits and providing design insights.

Findings

CRBs accurately predict estimation limits in near-field scenarios

Explicit scaling laws show the impact of array size and target range

Near-field corrections become significant for large arrays and close targets

Abstract

Extremely large-scale antenna arrays (ELAAs) envisioned for 6G enable high-resolution sensing. However, the ELAAs worked in extremely high frequency will push operation into the near-field region, where spherical wavefronts invalidate classical far-field models and alter fundamental estimation limits. The purpose of this and the companion paper (Part II) is to develop the theory of fundamental limits for near-field sensing systems in detail. In this paper (Part I), we develop a unified narrow-band near-field signal model for joint parameter sensing of moving targets using the ELAAs. Leveraging the Slepian--Bangs formulation, we derive closed-form Cram'er--Rao bounds (CRBs) for joint estimation of target position, velocity, and radar cross-section (RCS) under the slow-time sampling model. To obtain interpretable insights, we further establish explicit far-field and near-field approximations that reveal how the bounds scale with array aperture, target range, carrier wavelength, and coherent integration length. The resulting expressions expose the roles of self-information terms and their cross terms, clarifying when Fresnel corrections become non-negligible and providing beamformer and algorithm design guidelines for near-field sensing with ELAAs. Simulation results validate the derived CRBs and their far-field and near-field approximations, demonstrating accurate agreement with the analytical scaling laws across representative array sizes and target ranges.