Publikace
Nonlinear State Estimation with Missing Observations Based on Mathematical Programming
Typ:
Konferenční příspěvek
Název sborniku:
Abstracts of contributions of the 6th Int. Workshop on Data - Algorithms - Decision Making 2010
Klíčová slova:
state filtering, bounded errors, missing measurements
Anotace:
The contribution deals with two problems in the state estimation: a bounded uncertainty and missing measurement data. A discrete time state-space model with uniformly distributed uncertainty is considered. The Bayesian approach is used and maximum a posteriori probability estimates are evaluated. An estimation algorithm is based on the non-linear programming.