  We consider multiple-input multiple-output (MIMO) radar systems with
widely-spaced antennas. Such antenna configuration facilitates capturing the
inherent diversity gain due to independent signal dispersion by the target
scatterers. We consider a new MIMO radar framework for detecting a target that
lies in an unknown location. This is in contrast with conventional MIMO radars
which break the space into small cells and aim at detecting the presence of a
target in a specified cell. We treat this problem through offering a novel
composite hypothesis testing framework for target detection when (i) one or
more parameters of the target are unknown and we are interested in estimating
them, and (ii) only a finite number of observations are available. The test
offered optimizes a metric which accounts for both detection and estimation
accuracies. In this paper as the parameter of interest we focus on the vector
of time-delays that the waveforms undergo from being emitted by the transmit
antennas until being observed by the receive antennas. The analytical and
empirical results establish that for the proposed joint target detection and
time-delay estimation framework, MIMO radars exhibit significant gains over
phased-array radars for extended targets which consist of multiple independent
scatterers. For point targets modeled as single scatterers, however, the
detection/estimation accuracies of MIMO and phased-array radars for this
specific setup (joint target detection and time-delay estimation) are
comparable.
