Joint Range-Angle Estimation in Near-Field ISAC System using Uniform Circular Array

TL;DR

This paper develops a joint range-angle estimation framework for near-field ISAC systems using a uniform circular array, deriving CRLB, designing beamformers, and analyzing trade-offs between array size and SNR.

Contribution

It introduces a continuous-time channel model for NF ISAC with UCA, derives the CRLB, and proposes an optimal beamformer and ML estimator for joint range-angle estimation.

Findings

Larger UCA radius improves CRLB but reduces SNR, affecting practical estimation.

R = 0.5 m UCA achieves optimal balance between estimation accuracy and SNR.

Monte Carlo simulations validate the theoretical trade-offs and estimator performance.

Abstract

This paper studies joint range-angle estimation and communication in the NF ISAC systems, where the BS serves a single UE whose position is simultaneously estimated via monostatic sensing. Unlike the ULA, the UCA provides an angle-invariant NF region due to its rotational symmetry. To capture the full wideband NF propagation environment, we develop a continuous-time channel model incorporating per-element delay, Doppler shifts, and spherical wavefront geometry under OFDM signaling. Building on this model, we derive the closed-form CRLB for joint range-angle estimation of the UE position, design an optimal transmit beamformer via Riemannian gradient descent, and formulate a joint range-angle ML estimator. Monte Carlo simulations confirm a fundamental aperture-versus-SNR trade-off in NF-ISAC: while a larger UCA radius tightens the CRLB, it simultaneously reduces the received SNR at any given distance, pushing the maximum likelihood estimator below its convergence threshold and degrading practical performance. Among the evaluated configurations, R = 0.5 m achieves the best joint estimation and communication performance at the BS} by sustaining the highest received SNR throughout the evaluated range.