Joint Near-Field Sensing and Visibility Region Detection with Extremely Large Aperture Arrays

TL;DR

This paper introduces a novel joint sensing and visibility detection method for near-field localization using large aperture arrays, accounting for blockage and non-stationarity, with an Ising model and optimized algorithms.

Contribution

It presents a new approach combining Ising model characterization and alternating optimization for improved near-field sensing and blockage detection.

Findings

Effective detection of visibility regions in simulations

Improved localization accuracy over conventional methods

Robustness to partial array blockage

Abstract

In this paper, we consider near-field localization and sensing with an extremely large aperture array under partial blockage of array antennas, where spherical wavefront and spatial non-stationarity are accounted for. We propose an Ising model to characterize the clustered sparsity feature of the blockage pattern, develop an algorithm based on alternating optimization for joint channel parameter estimation and visibility region detection, and further estimate the locations of the user and environmental scatterers. The simulation results confirm the effectiveness of the proposed algorithm compared to conventional methods.