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Forward-Backward Map Matching for Airborne Magnetic Anomaly Navigation — arXiv:2610.38047

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.38047
License (as archived): CC0-1.0
Archived: 2026-11-01T02:45:54.238Z
SHA-256 of the archived text: ea5aada46ebd5d05443b6ffd2c974c22cca7a1311576cd5f580fe74169b23f56
Stable URL of this page: https://metraipolis.com/documento/dc_bb7dfb44a178

How to cite

Forward-Backward Map Matching for Airborne Magnetic Anomaly Navigation — arXiv:2610.38047 — arXiv (en), https://arxiv.org/abs/2610.38047 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_bb7dfb44a178 (Metraipolis archive dc_bb7dfb44a178, sha256 ea5aada46ebd5d05443b6ffd2c974c22cca7a1311576cd5f580fe74169b23f56)

BibTeX

@misc{dcbb7dfb44a178,
  title = {Forward-Backward Map Matching for Airborne Magnetic Anomaly Navigation — arXiv:2610.38047},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.38047},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_bb7dfb44a178; sha256 ea5aada46ebd5d05443b6ffd2c974c22cca7a1311576cd5f580fe74169b23f56},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.38047. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Airborne magnetic anomaly navigation provides a passive, unjammable alternative to Global Navigation Satellite Systems positioning by matching magnetometer measurements against a lithospheric magnetic anomaly map. Existing map-matching algorithms either assume a Gaussian posterior (extended Kalman filter), require Monte Carlo sampling (particle filter), or discard posterior uncertainty in favour of a single optimal path (Viterbi algorithm). Here we formulate map matching as inference on a chain-structured factor graph and solve it segment by segment using the forward-backward algorithm, which yields a discrete posterior over candidate positions and its Shannon entropy $H_t$ at time $t$. Over the \texttt{Renfrew\_395} map, $10^3$ synthetic trials yield a median position error of $32.7$ m, $91\%$ below the median inertial drift of $362$ m. On these trials and $10^3$ flight paths, the median error is $43\%$ below the extended Kalman filter and particle filter. Across these paths, a threshold on segment-level entropy detects $47\%$ of segments with errors above two map cells and $94\%$ of those above three, at a $10\%$ false-alarm rate. The foregoing results indicate that $H_t$ provides a truth-free diagnostic of map-conditioned navigation ambiguity.

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv cs.RO, nuovi lavori del giorno).
Categorie arXiv: Signal Processing (eess.SP) ; Robotics (cs.RO); Geophysics (physics.geo-ph).
Pagina del lavoro: https://arxiv.org/abs/2610.38047 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-01T02:16:58.693Z dalla pagina https://arxiv.org/list/cs.RO/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).