Bayesian statistical approaches to tracking through turbulence

Authors

Ben G. FitzpatrickFollow
Sarah McCanless
Yun Wang

Document Type

Conference Proceeding

Publication Date

2004

Abstract

We describe two Bayesian approaches for tracking through turbulence. The problem considered involves an extended target actively illuminated with several lasers. The returned imagery is used to infer atmospheric tilt. The main application of this technology is the control of a steering mirror, which is used to point a laser weapon at the target. Several model-based approaches are examined, including an optical transfer function model and a tilted reference image model.

Comments

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Original Publication Citation

Fitzpatrick, Ben & McCanless, S. & Wang, Yun. (2004). Bayesian statistical approaches to tracking through turbulence. Proceedings of the American Control Conference. 2. 1499 - 1503 vol.2.

Digital Commons @ LMU & LLS Citation

Fitzpatrick, Ben G.; McCanless, Sarah; and Wang, Yun, "Bayesian statistical approaches to tracking through turbulence" (2004). Mathematics, Statistics and Data Science Faculty Works. 188.
https://digitalcommons.lmu.edu/math_fac/188