  In this paper, we propose a sub-Nyquist sampling (SNS) orthogonal
frequency-division multiplexing (OFDM) radar system capable of reducing the
analog-to-digital converter (ADC) sampling rate in OFDM radar without any
additional manipulations of its hardware and waveform. To this end, the
proposed system utilizes the ADC sampling rate of B/L to sample the received
baseband signal with a bandwidth of B, where L is a positive proper divisor of
the number of subcarriers. This divides the baseband signal into L sub-bands,
folding into a sub-Nyquist frequency band due to aliasing. By leveraging known
modulation symbols of the transmitted signal, the folded signal can be unfolded
to the full-band signal. This allows an estimation of target ranges with the
range resolution of the full signal bandwidth B without the degradation of the
maximum unambiguous range. During the signal-unfolding process, the signals
from other sub-bands remain as symbol-mismatch noise (SMN), which significantly
degrades the signal-to-noise ratio (SNR) of the detected targets. It also
causes weaker targets to be submerged under the noise in range profiles. To
resolve this, a symbol-mismatch noise cancellation (SMNC) technique is also
proposed, which reconstructs the interfering signals from the other sub-bands
using the detected targets and subtracts them from the unfolded signal. As a
result, the proposed sub-Nyquist sampling OFDM radar and corresponding signal
processing technique enable a reduction in the ADC sampling rate by the ratio
of L while incurring only a 10 log10 L increase in the noise due to noise
folding. This is validated through simulations and measurements with various
sub-sampling ratios.
