Constrained Tensor Decomposition for 2d DOA Estimation In Transmit Beamspace Mimo Radar with Subarrays

Feng Xu; Sergiy A. Vorobyov

ICASSP 2021accepted0 citations

Constrained Tensor Decomposition for 2d DOA Estimation In Transmit Beamspace Mimo Radar with Subarrays

Abstract

In this paper, a constrained tensor decomposition method that enables two dimensional (2D) direction of arrival (DOA) estimation for transmit beamspace (TB) Multiple-Input Multiple-Output (MIMO) radar with subarrays is proposed. Specifically, a higher-order tensor model is designed to collect the received signal for TB MIMO radar with multiple subarrays. By exploiting the inner structure of the factor matrix, the constrained tensor decomposition is conducted, and subsequently the target DOA is estimated. In addition, the angular information can also be computed by solving the minimization problem that originates from the second factor matrix to improve the robustness of the 2D DOA estimation. Simulation results validate the proposed approach.

BibTeX

@inproceedings{icassp2021_constrainedtenso,
  title = {Constrained Tensor Decomposition for 2d DOA Estimation In Transmit Beamspace Mimo Radar with Subarrays},
  author = {Feng Xu and Sergiy A. Vorobyov},
  booktitle = {ICASSP 2021},
  year = {2021}
}