Translator Disclaimer
5 September 2008 Self-tuning Kalman filter estimation of atmospheric warp
Author Affiliations +
Abstract
In our previous work we have demonstrated that the perceived wander of image intensities as seen through the "windows" of each pixel due to atmospheric turbulence can be modelled as a simple oscillator pixel-by-pixel and a linear Kalman filter (KF) can be finetuned to predict to a certain extent short term future deformations. In this paper, we are expanding the Kalman filter into a Hybrid Extended Kalman filter (HEKF) to fine tune itself by relaxing the oscillator parameters at each individual pixel. Results show that HEKF performs significantly better than linear KF.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Murat Tahtali, Andrew Lambert, and Donald Fraser "Self-tuning Kalman filter estimation of atmospheric warp", Proc. SPIE 7076, Image Reconstruction from Incomplete Data V, 70760F (5 September 2008); doi: 10.1117/12.795888; https://doi.org/10.1117/12.795888
PROCEEDINGS
12 PAGES


SHARE
Advertisement
Advertisement
Back to Top