  Recent years have witnessed growing interest in reduced cost radar systems
operating with low power. Multiple-input multiple-output (MIMO) radar
technology is known to achieve high performance sensing by probing with
multiple orthogonal waveforms. However, implementing a low cost low power MIMO
radar is challenging. One of the reasons for this difficulty stems from the
increased cost and power consumption required by analog-to-digital convertors
(ADCs) in acquiring the multiple waveforms at the radar receiver. In this work
we study reduced cost MIMO radar receivers restricted to operate with low
resolution ADCs. We design bit-limited MIMO radar (BiLiMO) receivers which are
capable of accurately recovering their targets while operating under strict
resolution constraints. This is achieved by applying an additional analog
filter to the acquired waveforms, and designing the overall hybrid
analog-digital system to facilitate target identification using task-based
quantization methods. In particular, we exploit the fact that the target
parameters can be recovered from a compressed representation of the received
waveforms. We thus tune the acquisition system to recover this representation
with minimal distortion, from which the targets can be extracted in digital,
and characterize the achievable error in identifying the targets. Our numerical
results demonstrate that the proposed BiLiMO receiver operating with a bit
budget of one bit per sample achieves target recovery performance which
approaches that of costly MIMO radars operating with unlimited resolution ADCs,
while substantially outperforming MIMO receivers operating only in the digital
domain under the same bit limitations.
