AbstractSuppose we are given multiple independent reports on the count and identification (class, type, allegiance) of objects that are present in a certain volume of interest. The reports are uncertain (random and non-specific) and collected with the probability of detection P d < 1 and the probability of false alarm P f > 0 . The problem is to estimate the actual number of objects and their true identity. Adopting the formalism of the belief function theory as interpreted by the transferable belief model (TBM), a solution is proposed which maximises the plausibility of the global assignment cost of identification reports. The proposed global cost of assignment is shown by Monte Carlo simulations to outperform its ad hoc alternatives.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Global cost of assignment in the TBM framework for association of uncertain ID reports


    Contributors:

    Published in:

    Publication date :

    2006-10-25


    Size :

    7 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Global cost of assignment in the TBM framework for association of uncertain ID reports

    Ristic, B. / Smets, P. | British Library Conference Proceedings | 2007



    Dominant pole assignment in linear uncertain systems

    Ashokkumar, C. / Homaifar, A. / Yedavalli, Rama | AIAA | 1996


    Control design for robust eigenstructure assignment in linear uncertain systems

    Wilson, R.F. / Cloutier, J.R. / Yedavalli, R.K. | Tema Archive | 1992


    Real-Time Multi-UAV Task Assignment in Dynamic and Uncertain Environments

    Bertuccelli, Luca / Choi, Han-Lim / Cho, Peter et al. | AIAA | 2009