Localizing users and mapping the environment using radio signals is a key task in emerging applications such as reliable, low-latency communications, location-aware security, and safety-critical navigation. Recently introduced multipath-based simultaneous localization and mapping (MP-SLAM) can jointly localize a mobile agent (i.e., the user) and the reflective surfaces (such as walls) in radio frequency (RF) environments with convex geometries. Most existing MP-SLAM methods assume that map features and their corresponding RF propagation paths are statistically independent. These existing methods neglect inherent dependencies that arise when a single reflective surface contributes to different propagation paths or when an agent communicates with more than one base station (BS).

In our paper [1], we propose a Bayesian MP-SLAM method for distributed MIMO systems that addresses this limitation. In particular, we make use of amplitude statistics to establish adaptive time-varying detection probabilities. Based on the resulting “soft” ray-tracing strategy, our method can fuse information across propagation paths in RF environments with nonconvex geometries. A Bayesian estimation method for the joint estimation of map features and agent position is established. Our method is validated using synthetic RF measurements in a challenging scenario with nonconvex geometry and capable of early detection of new surfaces solely through double-bounce paths. Our algorithm provides accurate localization and mapping estimates and attains the posterior Cramér-Rao lower bound (PCRLB) [2].

[1] Xuhong Li, Benjamin Deutschmann, Erik Leitinger, and Florian Meyer, “Adaptive Multipath-Based SLAM for Distributed MIMO Systems,” unpublished, submitted for publication to IEEE Trans. Wireless Commun. [Online]. Available: https://arxiv.org/abs/2506.21798

[2] Benjamin Deutschmann, Xuhong Li, Florian Meyer, and Erik Leitinger, “Posterior Cramér-Rao Bounds on Localization and Mapping Errors in Distributed MIMO SLAM,” unpublished, submitted for publication to Asilomar-25, [Online]. Available: https://arxiv.org/abs/2506.19957

Contact: Erik Leitinger
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