Localized data assimilation in the ionosphere-thermosphere using a sampled-data unscented Kalman filter
Physics and Astronomy
We apply the unscented Kalman filter (UKF) to data assimilation based on the vertical one-dimensional global ionosphere-thermosphere model, which models the highly coupled, strongly nonlinear Earth’s upper atmosphere. To reduce the computational complexity of UKF, we introduce a localized, sampled-data update scheme with frozen-intersample error covariance, and examine its performance through numerical simulation.
Link to Published Version
Kim, I. S., Pawlowski, D. J., Ridley, A. J., & Bernstein, D. S. (2008). Localized data assimilation in the ionosphere-thermosphere using a sampled-data unscented Kalman filter. In American Control Conference, IEEE (pp. 1849–1854). Seattle, WA: IEEE. Retrieved from http://www-personal.umich.edu/~dsbaero/library/ConferencePapers/ACC2008/GITMUKF.pdf