We consider the problem of estimating the angles of arrival (AOAs) of multiple sources from a single snapshot obtained by a set of non-coherent sub-arrays, i.e., while the antenna elements in each sub-array are coherent, each sub-array observes a different unknown phase. Previous relevant works are based on eigendecomposition of the sample covariance, which requires a large number of snapshots, or on combining the sub-arrays using non-coherent processing methods. In this paper, we propose a technique to estimate the sub-arrays phase offsets for a given AOAs hypothesis, which facilitates approximate maximum likelihood estimation of the AOAs from a single snapshot. Numerical experiments show that the proposed approach clearly outperforms non-coherent processing, and even attains the Cramér-Rao lower bound in various scenarios.
|Title of host publication||2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|State||Published - May 2020|
|Event||2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, Spain|
Duration: 4 May 2020 → 8 May 2020
|Name||ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|
|Conference||2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020|
|Period||4/05/20 → 8/05/20|
- Angle of arrival
- array processing
- maximum likelihood estimation
- multiple sources
- single snapshot.