A distributed Kalman smoother
نویسندگان
چکیده
منابع مشابه
A distributed Kalman smoother
Kalman smoothers obtain state estimates in a system with stochastic dynamics and measurement noise. We consider the smoothing problem in a distributed setting, present a cooperative smoothing algorithm for Gauss-Markov linear models, and provide a convergence analysis for the algorithm. An extension of the algorithm that maximizes the likelihood with respect to a sequence of state vectors subje...
متن کاملImproved Kalman Smoother technique
An improved Kalman Smoother for atmospheric inversions L. M. P. Bruhwiler, A. M. Michalak, W. Peters, D. F. Baker, and P. Tans NOAA Climate Monitoring and Diagnostics Laboratory, Boulder, Colorado, USA Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan, USA Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, ...
متن کاملThe Variational Kalman Smoother
Abstract In this note we outline the derivation of the variational Kalman smoother, in the context of Bayesian Linear Dynamical Systems. The smoother is an efficient algorithm for the E-step in the ExpectationMaximisation (EM) algorithm for linear-Gaussian state-space models. However, inference approximations are required if we hold distributions over parameters. We derive the E-step updates fo...
متن کاملAFixed-Lag Kalman Smoother for RetrospectiveData Assimilation
Data assimilation has traditionally been employed to provide initial conditions for numerical weather prediction (NWP). A multi{year time sequence of objective analyses produced by data assimilation can also be used as an archival record from which to carry out a variety of atmospheric process studies. For this latter purpose, NWP analyses are not as accurate as they could be, for each analysis...
متن کاملThe Analog Ensemble Kalman Filter and Smoother
In classical data assimilation using sequential Monte Carlo methods, a physical model is run at each time steps to simulate members corresponding to different forecast scenarios. In this paper, we propose to use statistical analogs provided by observational or model-simulated data to emulate the dynamical model and generate relevant forecast members. This new methodology is called AnEnKF/AnEnFS...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IFAC Proceedings Volumes
سال: 2009
ISSN: 1474-6670
DOI: 10.3182/20090924-3-it-4005.00023