0357970 20240103195019.920110404235959.9 Praha ÚTIA AV ČR, v.v.i 2011 15 s. Research Report 2296 state-space model filtering bounded noise incomplete data cav_un_auth*0101175 Pavelková Lenka Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Department of Adaptive Systems Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2011/AS/pavelkova-state estimation with missing data and bounded uncertainty.pdf 1M0572 GA MŠk cav_un_auth*0001814 CEZ:AV0Z10750506 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. 2012 BC 4 O 4o 20231122134504.5 http://hdl.handle.net/11104/0196130 2011 Soubory v repozitáři: 0357970.pdf 2011 Praha ÚTIA AV ČR, v.v.i