Doppler Exploitation in Bistatic mmWave Radio SLAM

TL;DR

This paper investigates how Doppler information can enhance mmWave SLAM in 5G networks by deriving bounds and proposing a filtering solution, showing that Doppler improves localization and mapping accuracy.

Contribution

It introduces a novel approach to incorporate Doppler measurements into SLAM, including theoretical bounds and a sequential filtering algorithm, which were not previously considered.

Findings

Doppler information improves SLAM accuracy.

Theoretical PCRB analysis confirms benefits of Doppler.

Simulation results demonstrate enhanced localization performance.

Abstract

Networks in 5G and beyond utilize millimeter wave (mmWave) radio signals, large bandwidths, and large antenna arrays, which bring opportunities in jointly localizing the user equipment and mapping the propagation environment, termed as simultaneous localization and mapping (SLAM). Existing approaches mainly rely on delays and angles, and ignore the Doppler, although it contains geometric information. In this paper, we study the benefits of exploiting Doppler in SLAM through deriving the posterior Cram\'er-Rao bounds (PCRBs) and formulating the extended Kalman-Poisson multi-Bernoulli sequential filtering solution with Doppler as one of the involved measurements. Both theoretical PCRB analysis and simulation results demonstrate the efficacy of utilizing Doppler.