  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.
