  In this article, we present system design of D-band multi-input multi-output
(MIMO) frequency-modulated continuous-wave (FMCW) radar for indoor wireless
sensing. A uniform rectangular array (URA) of radar elements is used for 2D
direction-of-arrival (DOA) estimation. The DOA estimation accuracy of the MIMO
radar array in the presence of noise is evaluated using the multiple-signal
classification (MUSIC) and the minimum variance distortionless response (MVDR)
algorithms. We investigate different scaling scenarios for the radar receiver
(RX) SNR and the transmitter (TX) output power with the target distance. The
DOA estimation algorithm providing the highest accuracy and shortest simulation
time is shown to depend on the size of the radar array. Specifically, for a
64-element array, the MUSIC achieves lower root-mean-square error (RMSE)
compared to the MVDR across 1--10\,m indoor distances and 0--30\,dB SNR (e.g.,
$\rm 0.8^{\circ}$/$\rm 0.3^{\circ}$ versus $\rm 1.0^{\circ}$/$\rm 0.5^{\circ}$
at 10/20\,dB SNR and 5\,m distance) and 0.5x simulation time. For a 16-element
array, the two algorithms provide comparable performance, while for a 4-element
array, the MVDR outperforms the MUSIC by a large margin (e.g., $\rm
8.3^{\circ}$/$\rm 3.8^{\circ}$ versus $\rm 62.2^{\circ}$/$\rm 48.8^{\circ}$ at
10/20\,dB SNR and 5\,m distance) and 0.8x simulation time. Furthermore, the TX
output power requirement of the radar array is investigated in free-space and
through-wall wireless sensing scenarios, and is benchmarked by the
state-of-the-art D-band on-chip radars.
