Počet záznamů: 1

Vehicle position estimation using GPS/CAN data based on nonlinear programming

  1. 1.
    0361020 - UTIA-B 2012 RIV GB eng C - Konferenční příspěvek (zahraniční konf.)
    Pavelková, Lenka
    Vehicle position estimation using GPS/CAN data based on nonlinear programming.
    Proceedings of the 13th IASTED International Conference on Intelligent Systems and Control. Cambridge: IASTED, 2011 - (Whidborne, J.; Willis, P.), s. 208-215. ISBN 978-0-88986-889-2.
    [13th IASTED International Conference on Intelligent Systems and Control. Cambridge (GB), 11.07.2011-13.07.2011]
    Grant CEP: GA MŠk(CZ) 1M0572; GA ČR GA102/08/0567
    Výzkumný záměr: CEZ:AV0Z10750506
    Klíčová slova: nonlinear state-space model * state filtering * incomplete data * bounded noise * vehicle position estimation
    Kód oboru RIV: BC - Teorie a systémy řízení
    http://library.utia.cas.cz/separaty/2011/AS/pavelkova-vehicle position estimation using gps-can data based on nonlinear programming.pdf http://library.utia.cas.cz/separaty/2011/AS/pavelkova-vehicle position estimation using gps-can data based on nonlinear programming.pdf

    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.
    Trvalý link: http://hdl.handle.net/11104/0198436