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In this paper, the underdetermined 2D-DOD and 2D-DOA estimation for bistaticcoprime EMVS-MIMO radar is considered. Firstly, a 5-D tensor model wasconstructed by using the multi-dimensional space-time characteristics of thereceived data. Then, an 8-D tensor has been obtained by using theauto-correlation calculation. To obtain the difference coarrays of transmit andreceive EMVS, the de-coupling process between the spatial response of EMVS andthe steering vector is inevitable. Thus, a new 6-D tensor can be constructedvia the tensor permutation and the generalized tensorization of the canonicalpolyadic decomposition. {According} to the theory of the Tensor-Matrix Productoperation, the duplicated elements in the difference coarrays can be removed bythe utilization of two designed selection matrices. Due to the centrosymmetricgeometry of the difference coarrays, two DFT beamspace matrices weresubsequently designed to convert the complex steering matrices into thereal-valued ones, whose advantage is to improve the estimation accuracy of the2D-DODs and 2D-DOAs. Afterwards, a third-order tensor with the third-way fixedat 36 was constructed and the Parallel Factor algorithm was deployed, which canyield the closed-form automatically paired 2D-DOD and 2D-DOA estimation. Thesimulation results show that the proposed algorithm can exhibit superiorestimation performance for the underdetermined 2D-DOD and 2D-DOA estimation.

Underdetermined 2D-DOD and 2D-DOA Estimation for Bistatic Coprime EMVS-MIMO Radar: From the Difference Coarray Perspective