  Integrated sensing and communication (ISAC) is emerging as a key technique
for next-generation wireless systems. In order to expedite the practical
implementation of ISAC in pervasive mobile networks, it is crucial to have
widely deployed base stations with radar sensing capabilities. Thus, the
utilization of standardized multiple-input multiple-output (MIMO) orthogonal
frequency division multiplexing (OFDM) hardware architectures and waveforms is
pivotal for realizing seamless integration of effective communication and
sensing functionalities. In this paper, we introduce a novel joint
angle-range-velocity estimation algorithm for MIMO-OFDM ISAC systems. This
approach exclusively depends on the format of conventional MIMO-OFDM waveforms
that are widely adopted in wireless communications. Specifically, the
angle-range-velocity information of potential targets is jointly extracted by
utilizing all the received echo signals within a coherent processing interval
(CPI). The proposed joint estimation algorithm can achieve larger
signal-to-noise-ratio (SNR) processing gains and higher resolution by fully
exploiting the echo signals and jointly estimating the angle-range-velocity
information. A theoretical analysis for maximum unambiguous range, resolution,
and SNR processing gains is provided to verify the advantages of the proposed
joint estimation algorithm. Finally, the results of extensive numerical
experiments are presented to demonstrate that the proposed joint estimation
approach can achieve significantly lower root-mean-square-error (RMSE)
performance for angle/range/velocity estimation for both single- and
multi-target scenarios.
