0361020 20240103195334.920110719235959.9 8 s. CD cav_un_epca*0361019978-0-88986-889-2208-215CambridgeIASTED2011WhidborneJ. F.WillisP. nonlinear state-space model state filtering incomplete data bounded noise vehicle position estimation 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-vehicle position estimation using gps-can data based on nonlinear programming.pdf 1M0572 GA MŠk CZ cav_un_auth*0001814 GA102/08/0567 GA ČR cav_un_auth*0239566 CEZ:AV0Z10750506 The paper solves a problem of the estimation of the moving vehicle position. The position is measured by global position system (GPS) but outages sometimes occur in the measurements. During these outages, the actual position is estimated using data from vehicle sensors. A moving vehicle is described by a discrete-time state-space model with bounded noise. This model is constructed using kinematics laws and it can be used for arbitrary type of ground vehicle. Bayesian approach is applied to obtain position estimates. The maximum a posteriori (MAP) estimation converts to the nonlinear programming. The paper also discusses a setting of initial conditions for successful running of estimation process. cav_un_auth*0273076 13th IASTED International Conference on Intelligent Systems and Control Cambridge 11.07.2011-13.07.2011 GB 2012 BC http://hdl.handle.net/11104/0198436 2011 cav_un_epca*0361019 Proceedings of the 13th IASTED International Conference on Intelligent Systems and Control 978-0-88986-889-2 208 215 Proceedings of the 13th IASTED International Conference on Intelligent Systems and Control Cambridge IASTED 2011 Whidborne J. F. 340 Willis P. 340