{
  "abstract": "In Integrated Sensing and Communications (ISAC), radar sensing must operate under chirp subsampling with up to 90\\% missing data. An attention-based baseline, limited to a 52~ms buffer, collapses toward maximum uniform entropy ($H=2.584$ bits) as sparsity increases, failing to capture long-range gait-cycle context. We propose StarBOA, which replaces attention with a causal Mamba state-space model that updates incrementally on a per-window basis without re-scanning past reconstructions. By maintaining a persistent state, StarBOA integrates over $100\\times$ more temporal history at no additional per-step computational cost. StarBOA outperforms the baseline's published results across all sparsity levels, with SSIM gains increasing from $+0.0379$ at 50\\% missing data to $+0.2472$ at 90\\%. Each window is processed in 1.53~ms with zero lookahead, demonstrating efficient causal reconstruction under extreme chirp subsampling.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.33408",
  "author_total": 3,
  "authors": [
    {
      "name": "Mustafa Bora Çelik"
    },
    {
      "name": "Ceren Çelik"
    },
    {
      "name": "Orhan Gazi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6sr7c3ypnc4kr.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.33408",
  "fulltext_url": null,
  "id": "6sr7c3ypnc4kr",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.33408",
  "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",
      "cs.LG"
    ],
    [
      "arxiv",
      "cs.NI"
    ],
    [
      "arxiv",
      "math.IT"
    ],
    [
      "openalex",
      "2202|Advanced SAR Imaging Techniques"
    ]
  ],
  "openalex": "W7214728321",
  "pdf_url": "https://arxiv.org/pdf/2609.33408",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6sr7c3ypnc4kr.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:17Z",
      "native_id": "2609.33408",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.33408"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "StarBOA: Real-Time Mamba State-Space Unrolling for Sparse Radar Micro-Doppler in ISAC Networks",
  "title_text": "StarBOA: Real-Time Mamba State-Space Unrolling for Sparse Radar Micro-Doppler in ISAC Networks",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:17Z",
  "url": "https://research.draconitic.com/paper/6sr7c3ypnc4kr",
  "venue": "arXiv",
  "versions": []
}