Exploiting Double-Bounce Paths in Snapshot Radio SLAM: Bounds, Algorithms and Experiments

TL;DR

This paper explores the use of double-bounce NLoS radio paths in SLAM to improve localization and environmental mapping, deriving bounds, proposing algorithms, and validating with simulations and real measurements.

Contribution

It introduces a novel approach to leverage double-bounce NLoS paths in radio SLAM, including bounds derivation and path identification algorithms, enhancing accuracy and mapping.

Findings

Double-bounce NLoS paths improve localization accuracy.

Exploiting double-bounce paths reveals previously unobservable landmarks.

Algorithms validated with mmWave 5G measurements show significant benefits.

Abstract

Radio-based simultaneous localization and mapping (SLAM) has the potential to provide precise user equipment (UE) localization and environmental sensing capabilities by exploiting radio signals. Most existing approaches leverage line-of-sight (LoS) and single-bounce non-line-of-sight (NLoS) paths solely, while higher-order NLoS paths are treated as disturbance. In this paper, we investigate the benefits of leveraging double-bounce NLoS paths for solving the bistatic snapshot radio SLAM problem. We derive the Cramer-Rao bound (CRB) for joint estimation of the UE state and landmark positions when double-bounce NLoS paths are present. In addition, we propose an algorithm to identify double-bounce NLoS paths and leverage them into joint UE and landmarks estimation. The derived bounds are validated through simulated data, and the proposed algorithms are evaluated using experimental millimeter wave (mmWave) measurements harnessing beamformed 5G cellular reference signals. The numerical and experimental results demonstrate that the double-bounce NLoS paths which share at least one incidence point (IP) with the single-bounce NLoS paths improve the estimation accuracy of the UE state and existing IPs of single-bounce NLoS paths. Importantly, exploiting double-bounce NLoS paths enhances environmental mapping capabilities by revealing landmarks that are unobservable with single-bounce NLoS paths alone.