Star tracker using vector-based deep learning for enhanced performance
US11851217B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 17, 2020 |
| Grant date | Dec 26, 2023 |
| Priority date | — |
| Expiry date | Aug 15, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
Star tracker systems and methods are provided. The star tracker incorporates deep learning processes in combination with relatively low cost hardware components to provide moderate (e.g. ˜1 arc second attitude uncertainty) accuracy. The neural network implementing the deep learning processes can include a Hinton's capsule network or a coordinate convolution layer to maintain spatial relationships between features in images encompassing a plurality of features. The hardware components can be configured to collect a blurred or defocused image in which point sources of light appear as blurs, and in which the blurs create points of intersection. Alternatively or in addition, a blurred or defocused image can be created using processes implemented as part of application programming. The processing of collected images by a neural network to provide an attitude determination can include analyzing a plurality of blurs and blur intersections across an entire frame of image data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.