Resolution-Aliasing Trade-off in Near-Field Localisation

TL;DR

This paper analyzes the trade-off between resolution and aliasing in near-field localisation for XL-MIMO systems, providing a unified framework and practical design guidelines for array configurations.

Contribution

It introduces a unified analytical framework linking array geometry and sampling density to resolution and aliasing, with novel tools for array design.

Findings

Resolution and aliasing are not always coupled; increasing aperture can improve resolution without increasing aliasing.

Analytical expressions relate array geometry to spatial bandwidth and aliasing.

Practical guidelines for array design to balance resolution and aliasing in near-field localisation.

Abstract

Extremely Large-scale MIMO (XL-MIMO) systems operating in Near-Field (NF) introduce new degrees of freedom for accurate source localisation, but make dense arrays impractical. Sparse or distributed arrays can reduce hardware complexity while maintaining high resolution, yet sub-Nyquist spatial sampling introduces aliasing artefacts in the localisation ambiguity function. This paper presents a unified framework to jointly characterise resolution and aliasing in NF localisation and study the trade-off between the two. Leveraging the concept of local chirp spatial frequency, we derive analytical expressions linking array geometry and sampling density to the spatial bandwidth of the received field. We introduce two geometric tools--Critical Antenna Elements (CAEs) and the Non-Contributive Zone (NCZ)--to intuitively identify how individual antennas contribute to resolution and/or aliasing. Our analysis reveals that resolution and aliasing are not always strictly coupled, e.g., increasing the array aperture can improve resolution without necessarily aggravating aliasing. These results provide practical guidelines for designing NF arrays that optimally balance resolution and aliasing, supporting efficient XL-MIMO deployment.