A Simplified Time-varying Kalman Filter For A Large Scale Air Pollution Model
Free (open access)
X.F. Zhang, A.W. Heemink, L.H.J.M. Janssen P.H.M. Janssen & F.J. Sauted
A simplified time-varying Kalman filter for a large scale air pollution model X.F. Zhang*, A.W. HeeminkL.H.J.M. Janssen^ P.H.M. Janssen^ & F.J. Sauted ^Department of Technical Mathematics and Informatics. Delft University of Tbchnoiogy, MeWweg 4. P.O. Box 5031 2600 GA Delft. Tie Netherlands ^National Institute of Public Health and Environmental Pro- tection, P.O. Box 1, 3720 BA Bilthoven, The Netherlands 1 Introduction In [1-3] a tim-in variant filter approximation and a smoother approximation to the evaluation of the methane (CH±) distribution in the atmosphere of Europe, has been developed. To avoid the heavy computation burden and huge storage requirement of the conventional Kalman filter for large scale systems, the Chandrasekhar-type filter algorithm and the Reduced Rank Square Root (RRSQRT) filter algorithm are employed in each approach. This paper reports on a time-varying Kalman filter for the accurate estima- tion of the C//4 distribution in the atmosphere of Europe.