Web projektu DAR

Výzkumné centrum
Data - Algoritmy - Rozhodování

Založeno v roce 2005 s podporou MŠMT ČR (projekt 1M0572)

Publikace

State estimation with missing data and bounded uncertainty

Typ:

Výzkumná zpráva

Autoři publikace:

Pavelková L.

Název edice:

Research Report

Číslo zprávy:

2296

Nakladatel:

ÚTIA AV ČR, v.v.i

Místo vydání:

Praha

Rok:

2011

Kontaktní osoba:

Ing. Lenka Pavelková, Ph.D. (ÚTIA - Oddělení adaptivních systémů)

Klíčová slova:

state-space model, filtering, bounded noise, incomplete data

Anotace:

The paper deals with two problems in the state estimation: (i) bounded uncertainty and (ii) missing measurement data. An algorithm for the state estimation of the discrete-time state space model whose uncertainties are bounded is proposed here. The algorithm also copes with situations when some data for identification are missing. The Bayesian approach is used and maximum a posteriori probability estimates are evaluated in the discrete time instants. The proposed estimation algorithm is applied to the estimation of vehicle position when incomplete data from global positioning system together with complete data from the inertial measurement unit are at disposal.