  Uplink sensing in perceptive mobile networks (PMNs), which uses uplink
communication signals for sensing the environment around a base station, faces
challenging issues of clock asynchronism and the requirement of a line-of-sight
(LOS) path between transmitters and receivers. The channel state information
(CSI) ratio has been applied to resolve these issues, however, current research
on the CSI ratio is limited to Doppler estimation in a single dynamic path.
This paper proposes an advanced parameter estimation scheme that can extract
multiple dynamic parameters, including Doppler frequency, angle-of-arrival
(AoA), and delay, in a communication uplink channel and completes the
localization of multiple moving targets. Our scheme is based on the
multi-element Taylor series of the CSI ratio that converts a nonlinear function
of sensing parameters to linear forms and enables the applications of
traditional sensing algorithms. Using the truncated Taylor series, we develop
novel multiple-signal-classification grid searching algorithms for estimating
Doppler frequencies and AoAs and use the least-square method to obtain delays.
Both experimental and simulation results are provided, demonstrating that our
proposed scheme can achieve good performances for sensing both single and
multiple dynamic paths, without requiring the presence of a LOS path.
