LOCUS-DT: Digital-Twin Posterior Localization

projects

I lead LOCUS-DT, a wireless-localization framework that compares an observed multipath snapshot with candidate-specific signatures generated by a ray-tracing wireless digital twin. The learned compatibility scores form a posterior over transmitter location, including multiple plausible modes when the measurement is incomplete or the model is imperfect.

Observation-conditioned digital-twin inference

For every candidate location, the digital twin supplies the multipath structure that the receiver would expect. LOCUS-DT scores the agreement between those simulated hypotheses and the measured path peaks, then normalizes the scores into a calibrated spatial belief.

LOCUS-DT framework connecting a real RF snapshot, a wireless-digital-twin candidate library, learned compatibility scoring, and the resulting location posterior.
Journal schematic. LOCUS-DT matches measured multipath features with candidate-specific ray-traced signatures and converts their learned compatibility into a transmitter-location posterior.
LOCUS-DT posterior localization results in three unseen indoor layouts.
Conference evidence. Experiments across three unseen indoor layouts recover structured, often multimodal posteriors that expose blockage and multipath instead of hiding them behind one coordinate.

The peer-reviewed IEEE GLOBECOM 2026 paper establishes LOCUS-DT. The first- and corresponding-author journal extension, Site-Agnostic Posterior Inference for Indoor Localization with Ray-Tracing Wireless Digital Twins, studies site generalization and explicit digital-twin mismatch; a revision is in preparation for resubmission to IEEE Transactions on Wireless Communications (TWC).

Relationship to MC-CLE

LOCUS-DT and MC-CLE share a full-posterior localization objective but use complementary models. LOCUS-DT explicitly evaluates observed multipath against ray-traced candidate signatures; MC-CLE learns a measurement-conditioned candidate likelihood. Their common output is calibrated spatial belief that can support localization, multi-view fusion, and active sensing.

Wireless Localization Digital Twins Probabilistic Inference