{
  "abstract": "Near-field to far-field transformation is central to large-aperture antenna testing, yet two coupled challenges remain: costly phase acquisition at millimeter-wave bands and violations of the centering assumption under offset mounting. Existing methods address these issues separately, requiring either dense full-field data or offset vectors. We tackle both jointly by exploiting a key observation: amplitude fields under different offsets are coordinate-transformed views of the same near field. The challenge is to recover the center-aligned field from offset amplitudes without a phase or offset vector. We propose AntennaFlow, a three-stage framework: a contrastively learned encoder that maps offset views to an offset-invariant embedding, a deterministic flow-matching transport that maps offset amplitudes to center-aligned ones, and the Simplified Extrapolation Technique, whose Green-function Taylor expansion is valid only for centered fields. Experiments show that AntennaFlow enables fast, phaseless, offset-vector-free NF--FF reconstruction from sparse amplitude-only measurements, consistently outperforming existing baselines while preserving physical consistency.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.16948",
  "author_total": 5,
  "authors": [
    {
      "name": "Yongzhi Li"
    },
    {
      "name": "Chongting Shen"
    },
    {
      "name": "Menglin Chen"
    },
    {
      "name": "Xun Jiang"
    },
    {
      "name": "Zhengpeng Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/e8nz4zkwxjppy.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.16948",
  "fulltext_url": null,
  "id": "e8nz4zkwxjppy",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.16948",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.AI"
    ],
    [
      "arxiv",
      "cs.IT"
    ],
    [
      "arxiv",
      "math.IT"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2609.16948",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-15",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/e8nz4zkwxjppy.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:45Z",
      "native_id": "2609.16948",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.16948"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "AntennaFlow: A Generative Flow Model for Offset Correction in Phaseless Antenna Testing",
  "title_text": "AntennaFlow: A Generative Flow Model for Offset Correction in Phaseless Antenna Testing",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:45Z",
  "url": "https://research.draconitic.com/paper/e8nz4zkwxjppy",
  "venue": "arXiv",
  "versions": []
}