# LOCUS-DT: Localization via Observation-Conditioned Uncertainty Scoring with Digital Twins

arXiv: https://arxiv.org/abs/2608.00406 · HTML: https://mlsanity.com/paper/2608.00406/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 26 references that are in the map.
- First posted on arXiv 1 Aug 2026.

## Builds on (most cited first, 12 of 12)

- [Digital Twin of Wireless Systems: Overview, Taxonomy, Challenges, and Opportunities](https://mlsanity.com/paper/2202.02559/) (2022)
- [LinCDE: Conditional Density Estimation via Lindsey's Method](https://mlsanity.com/paper/2107.12713/) (2021)
- [Digital Twin-Enhanced Wireless Indoor Navigation: Achieving Efficient Environment Sensing with Zero-Shot Reinforcement Learning](https://mlsanity.com/paper/2306.06766/) (2023)
- [Reinforcement Learning with Physics-Informed Symbolic Program Priors for Zero-Shot Wireless Indoor Navigation](https://mlsanity.com/paper/2506.22365/) (2025)
- [ISAC Imaging by Channel State Information using Ray Tracing for Next Generation 6G](https://mlsanity.com/paper/2509.06672/) (2025)
- [Uncertainty Awareness in Wireless Communications and Sensing](https://mlsanity.com/paper/2412.14369/) (2024)
- [Site-Specific Location Calibration and Validation of Ray-Tracing Simulator NYURay at Upper Mid-Band Frequencies](https://mlsanity.com/paper/2507.22027/) (2025)
- [Angular Spread Statistics for 6.75 GHz FR1(C) and 16.95 GHz FR3 Mid-Band Frequencies in an Indoor Hotspot Environment](https://mlsanity.com/paper/2409.03013/) (2024)
- [HoRAMA: Holistic Reconstruction with Automated Material Assignment for Ray Tracing using NYURay](https://mlsanity.com/paper/2602.12942/) (2026)
- [Upper Mid-Band Channel Measurements and Characterization at 6.75 GHz FR1(C) and 16.95 GHz FR3 in an Indoor Factory Scenario](https://mlsanity.com/paper/2411.03565/) (2024)
- [Beyond Point Estimates: Likelihood-Based Full-Posterior Wireless Localization](https://mlsanity.com/paper/2509.25719/) (2025)
- [Transformer-Based Rate Prediction for Multi-Band Cellular Handsets](https://mlsanity.com/paper/2509.25722/) (2025)

## Abstract (arXiv)

Accurate indoor localization is essential for emerging applications in robotic navigation and search and rescue. While classical methods typically focus on single-point estimates, complex indoor environments with heavy blockage and multipath propagation often lead to multimodal likelihood surfaces where a single estimate is insufficient. This paper proposes LOCUS-DT (Localization via Observation-Conditioned Uncertainty Scoring with Digital Twins), a framework that treats snapshot localization as posterior inference over the transmitter location. By leveraging a ray-tracing-based digital twin (DT) of the known environment, LOCUS-DT generates synthetic multipath profiles for candidate locations and compares them against the measured channel profile. Central to our approach is a novel learned scoring function designed to compare a fixed number of dominant specular paths, providing robustness against errors in both the DT environment model and the physical channel estimation. Importantly, LOCUS-DT is trained over an ensemble of environments to ensure generalization to unseen layouts. We evaluate the system using a Sionna-based ray-tracing backend, demonstrating that LOCUS-DT captures the sharp, multimodal posterior structures inherent in indoor settings more accurately than standard Gaussian or Gaussian-mixture benchmarks.