- Title
- Optimising wavefront sensing super-resolution in the control of tomographic adaptive optics
- Creator
- Cranney, Jesse; Guihot, Angus; De Dona, Jose; Rigaut, Francois
- Relation
- 2021 Australian & New Zealand Control Conference, ANZCC 2021. 2021 Australian & New Zealand Control Conference (ANZCC) (Gold Coast, Australia 25-26 November, 2021) p. 24-29
- Publisher Link
- http://dx.doi.org/10.1109/ANZCC53563.2021.9628305
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2021
- Description
- In this work we propose to explore and optimise a novel concept in adaptive optics wavefront sensing. The notion being investigated is that of super-resolution, which is aimed at increasing spatial resolution in tomographic adaptive optics by introducing diversity in the alignment of different wavefront sensors. The optimisation of super-resolution requires efficient computation of the wavefront estimation error. A model of the wavefront sensor compatible with super-resolution is proposed in this paper, together with a suitable cost function to optimise the super-resolution geometry. We provide initial optimisation results verified by end-to-end simulations. In future work we will investigate the parallelisation of the optimisation routine, and alternative optimisation methods.
- Subject
- geometry; adaptation models; estimation error; computational modeling; superresolution; optimazation methods
- Identifier
- http://hdl.handle.net/1959.13/1449853
- Identifier
- uon:43762
- Identifier
- ISBN:9781665416511
- Identifier
- ISSN:2767-7230
- Language
- eng
- Reviewed
- Hits: 1447
- Visitors: 1447
- Downloads: 0
| Thumbnail | File | Description | Size | Format |
|---|