  We propose Tensor-based 4D Sub-Nyquist Radar (TenDSuR) that samples in
spectral, spatial, Doppler, and temporal domains at sub-Nyquist rates while
simultaneously recovering the target's direction, Doppler velocity, and range
without loss of native resolutions. We formulate the radar signal model wherein
the received echo samples are represented by a partial third-order tensor. We
then apply compressed sensing in the tensor domain and use our tensor-OMP and
tensor completion algorithms for signal recovery. Our numerical experiments
demonstrate joint estimation of all three target parameters at the same native
resolutions as a conventional radar but with reduced measurements. Furthermore,
tensor completion methods show enhanced performance in off-grid target recovery
with respect to tensor-OMP.
