Propagation Mechanism-Aware Near-Field Spatially Non-Stationary Channel Estimation and Environment Mapping

TL;DR

This paper introduces a unified model and algorithm for near-field channel estimation and environment mapping in large aperture arrays, accounting for spatial non-stationarity and complex propagation effects.

Contribution

It proposes a novel parametric sensing channel model and a GC-SAGE algorithm that jointly estimate channel parameters and map environment scatterers considering near-field effects.

Findings

Validated with ray-based simulation and field measurements.

Effectively detects channel spatial non-stationarity and environment scatterers.

Improves near-field channel estimation accuracy in ISAC systems.

Abstract

Extremely large aperture arrays (ELAAs) benefit the dual functions of integrated sensing and communication (ISAC) systems by enabling high-throughput data streams and high angular resolution with near-field spatial diversity. However, near-field spherical wavefront effects and spatial non-stationarity (SNS) bring challenges to both communication and sensing. This paper studies near-field spatially non-stationary channel estimation and environment mapping by jointly accounting for multi-bounce, blockage-induced partial visibility, and hybrid reflection-scattering propagation. We propose a unified parametric sensing channel model that represents the SNS phenomenon (due to partial array blockage, diffraction, and specular reflection) through spatially varying visibility and amplitude of each multipath across the array. To regularize the spatially varying delays caused by propagation mechanisms, we incorporate geometric constraints (GCs) based on environmental interaction points, embedding them into the model as absolute propagation delays. We then develop a GC-space-alternating generalized expectation-maximization (GC-SAGE) algorithm to estimate near-field channel parameters and locate environment scatterers/reflectors. Moreover, the GC-SAGE calculates per antenna path amplitudes based on the delays determined by the coordinates of scatterers/reflectors and transceivers, thereby effectively detecting channel SNS. Both ray-based simulation and field measurement are used to validate the proposed approach.