English

Single-Snapshot Localization Using Sparse Extremely Large Aperture Arrays

Signal Processing 2025-09-23 v1

Abstract

This paper investigates single-snapshot direction-of-arrival (DOA) estimation and target localization with coherent sparse extremely large aperture arrays (ELAAs) in automotive radar applications. Far-field and near-field signal models are formulated for distributed bistatic configurations. To enable noncoherent processing, a single-snapshot MUSIC (SS-MUSIC) algorithm is proposed to fuse local spectra from individual subarrays and extended to near-field localization via geometric intersection. For coherent processing, a single-snapshot ESPRIT (SS-ESPRIT) method with ambiguity dealiasing is developed to fully exploit the aperture of sparse ELAAs for high-resolution angle estimation. Simulation results demonstrate that SS-ESPRIT provides superior angular resolution for closely spaced far-field targets, while SS-MUSIC offers robustness in near-field localization and flexibility in hybrid scenarios.

Keywords

Cite

@article{arxiv.2509.17511,
  title  = {Single-Snapshot Localization Using Sparse Extremely Large Aperture Arrays},
  author = {Yunqiao Hu and Xuesu Xiao and Steven Jones and Shunqiao Sun},
  journal= {arXiv preprint arXiv:2509.17511},
  year   = {2025}
}

Comments

ICASSP 2026 manuscript under review

R2 v1 2026-07-01T05:49:06.738Z