ICASSP 2022accepted0 citations

Doa Estimation Via Coarray Tensor Completion with Missing Slices

Hang Zheng, Chengwei Zhou, André L. F. de Almeida, Yujie Gu, Zhiguo Shi

Abstract

In this paper, a coarray tensor completion-based direction-of-arrival (DOA) estimation method is proposed for coprime planar array. To perform Nyquist-matched coarray signal processing, the completion of the coarray tensor corresponding to an augmented discontinuous virtual array is pursued. However, it is difficult to impose a low-rank regularization on the incomplete coarray tensor with slices of missing elements for its completion. To solve this problem, a structural tensorization approach is designed to reshape the incomplete coarray tensor into one with distributed missing elements. As such, a coarray tensor completion problem based on tensor nuclear norm minimization is formulated to complete these missing elements. By exploiting the filled virtual array obtained from the completed coarray tensor, a super-resolution DOA estimation can be achieved in closed-form.

BibTeX
@inproceedings{icassp2022_doaestimationvia,
  title = {Doa Estimation Via Coarray Tensor Completion with Missing Slices},
  author = {Hang Zheng and Chengwei Zhou and André L. F. de Almeida and Yujie Gu and Zhiguo Shi},
  booktitle = {ICASSP 2022},
  year = {2022}
}
Doa Estimation Via Coarray Tensor Completion with Missing Slices · ICASSP 2022