Performance Bounds of Near-Field Sensing with Circular Arrays

TL;DR

This paper derives and analyzes the fundamental performance bounds for near-field sensing using circular arrays, highlighting how bandwidth and array size influence estimation accuracy and revealing that larger arrays do not always improve performance.

Contribution

The paper provides closed-form Cramer-Rao bounds for near-field sensing with circular arrays, including new insights into the effects of bandwidth and array size on estimation performance.

Findings

Enlarging array size does not always improve sensing accuracy.

Derived CRBs include existing results as special cases.

Numerical validation confirms the theoretical bounds.

Abstract

The performance bounds of near-field sensing are studied for circular arrays, focusing on the impact of bandwidth and array size. The closed-form Cramer-Rao bound (CRBs) for angle and distance estimation are derived, revealing the scaling laws of the CRBs with bandwidth and array size. Contrary to expectations, enlarging array size does not always enhance sensing performance. Furthermore, the asymptotic CRBs are analyzed under different conditions, unveiling that the derived expressions include the existing results as special cases. Finally, the derived expressions are validated through numerical results.