Share Email Print
cover

Proceedings Paper

Self-tuning Kalman filter estimation of atmospheric warp
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 5 September 2008
PDF: 12 pages
Proc. SPIE 7076, Image Reconstruction from Incomplete Data V, 70760F (5 September 2008); doi: 10.1117/12.795888
Show Author Affiliations
Murat Tahtali, Univ. of New South Wales, Australian Defence Force Academy (Australia)
Andrew Lambert, Univ. of New South Wales, Australian Defence Force Academy (Australia)
Donald Fraser, Univ. of New South Wales, Australian Defence Force Academy (Australia)


Published in SPIE Proceedings Vol. 7076:
Image Reconstruction from Incomplete Data V
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

© SPIE. Terms of Use
Back to Top