  In this paper, the underdetermined 2D-DOD and 2D-DOA estimation for bistatic
coprime EMVS-MIMO radar is considered. Firstly, a 5-D tensor model was
constructed by using the multi-dimensional space-time characteristics of the
received data. Then, an 8-D tensor has been obtained by using the
auto-correlation calculation. To obtain the difference coarrays of transmit and
receive EMVS, the de-coupling process between the spatial response of EMVS and
the steering vector is inevitable. Thus, a new 6-D tensor can be constructed
via the tensor permutation and the generalized tensorization of the canonical
polyadic decomposition. {According} to the theory of the Tensor-Matrix Product
operation, the duplicated elements in the difference coarrays can be removed by
the utilization of two designed selection matrices. Due to the centrosymmetric
geometry of the difference coarrays, two DFT beamspace matrices were
subsequently designed to convert the complex steering matrices into the
real-valued ones, whose advantage is to improve the estimation accuracy of the
2D-DODs and 2D-DOAs. Afterwards, a third-order tensor with the third-way fixed
at 36 was constructed and the Parallel Factor algorithm was deployed, which can
yield the closed-form automatically paired 2D-DOD and 2D-DOA estimation. The
simulation results show that the proposed algorithm can exhibit superior
estimation performance for the underdetermined 2D-DOD and 2D-DOA estimation.
