{
  "abstract": "Environment reconstruction for low-altitude integrated sensing and communications (ISAC) has largely focused on geometry-centric maps, overlooking material-dependent propagation effects. Material-labeled reconstruction is therefore a key step toward propagation-aware mapping, enabling more physically grounded channel prediction and uncrewed aerial vehicle (UAV) networking. However, constructing such maps from wireless multipath observations is challenging in outdoor multi-building scenarios because multipath components (MPCs) from different facades are mixed, path-to-facade attribution is uncertain, and UAV measurements arrive sequentially under time-varying observation geometries. To address these challenges, we propose a unified online probabilistic framework that represents each reflecting facade as a virtual anchor (VA) and couples Bayesian VA localization, multipath attribution, and material inference. The Bayesian front end estimates facade-level geometry and computes soft MPC-to-VA attribution probabilities using a speculardiffuse likelihood model, thereby accounting for both dominant specular paths and diffuse surface-interacted components. These attribution probabilities are used to construct attribution-aware MPC representations, which are aggregated in a VA-centric manner and mapped by a material inference network to facadelevel material evidence. The resulting evidence is recursively fused through an online Bayesian update to produce stable material posteriors and material-labeled environment maps. Ray-tracing simulations in a representative urban street scenario show that the proposed method substantially outperforms a no-attribution baseline, achieves 93.75% final facade-level material accuracy on a held-out UAV trajectory, and maintains accurate VA-based facade localization.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.19819",
  "author_total": 4,
  "authors": [
    {
      "name": "Meihui Liu"
    },
    {
      "name": "Shu Sun"
    },
    {
      "name": "Ruifeng Gao"
    },
    {
      "name": "Qiuming Zhu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2jsymj6papk80.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.19819",
  "fulltext_url": null,
  "id": "2jsymj6papk80",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.19819",
  "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.IT"
    ],
    [
      "arxiv",
      "math.IT"
    ],
    [
      "openalex",
      "2208|Millimeter-Wave Propagation and Modeling"
    ]
  ],
  "openalex": "W7213599527",
  "pdf_url": "https://arxiv.org/pdf/2609.19819",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-17",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/2jsymj6papk80.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:22:23Z",
      "native_id": "2609.19819",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.19819"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "Online Material-Labeled Environment Reconstruction via Bayesian Multipath Attribution for Low-Altitude ISAC",
  "title_text": "Online Material-Labeled Environment Reconstruction via Bayesian Multipath Attribution for Low-Altitude ISAC",
  "type": "preprint",
  "updated_at": "2026-10-30T12:22:23Z",
  "url": "https://research.draconitic.com/paper/2jsymj6papk80",
  "venue": "arXiv",
  "versions": []
}