Kalman Filter-based Sensing in Communication Systems with Clock Asynchronism

TL;DR

This paper introduces a Kalman Filter-based joint communication and sensing scheme for uplink systems that effectively mitigates clock asynchronism effects, improving localization accuracy without prior UE location knowledge.

Contribution

A novel KF-based scheme that enhances uplink sensing accuracy by compensating for clock asynchronism effects without requiring prior UE location information.

Findings

Localization RMSE is about 20 dB lower than benchmarks.

The scheme effectively suppresses time-varying noise in CSI.

Accurate UE and scatterer localization achieved.

Abstract

In this paper, we propose a novel Kalman Filter (KF)-based uplink (UL) joint communication and sensing (JCAS) scheme, which can significantly reduce the range and location estimation errors due to the clock asynchronism between the base station (BS) and user equipment (UE). Clock asynchronism causes time-varying time offset (TO) and carrier frequency offset (CFO), leading to major challenges in uplink sensing. Unlike existing technologies, our scheme does not require knowing the location of the UE in advance, and retains the linearity of the sensing parameter estimation problem. We first estimate the angle-of-arrivals (AoAs) of multipaths and use them to spatially filter the CSI. Then, we propose a KF-based CSI enhancer that exploits the estimation of Doppler with CFO as the prior information to significantly suppress the time-varying noise-like TO terms in spatially filtered CSIs. Subsequently, we can estimate the accurate ranges of UE and the scatterers based on the KF-enhanced CSI. Finally, we identify the UE's AoA and range estimation and locate UE, then locate the dumb scatterers using the bi-static system. Simulation results validate the proposed scheme. The localization root mean square error of the proposed method is about 20 dB lower than the benchmarking scheme.