In this paper, the problem of target tracking with glint noise is considered. We apply a radial basis function (RBF) neural network to evaluate the nonlinear score function, which is used as the correction term in the state estimation of robust Kalman filter. Simulation results are presented to demonstrate the performance of the evaluation of the score function.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Target tracking with glint noise using an RBF neural network


    Contributors:
    Wei Yan (author) / Zhaoda Zhu (author)


    Publication date :

    1996-01-01


    Size :

    326176 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Target Tracking with Glint Noise Using an RBF Neural Network

    Yan, W. / Zhu, Z. / IEEE; Dayton Section et al. | British Library Conference Proceedings | 1996


    Target Tracking With Glint Noise

    Wu, W.-R. | Online Contents | 1993


    Particle Filter for Ballistic Target Tracking with Glint Noise

    Kim, Jinwhan / Tandale, Monish / Menon, P. K. et al. | AIAA | 2010


    Particle Filter for Ballistic Target Tracking with Glint Noise

    Kim, J. / Tandale, M. / Menon, P. et al. | British Library Conference Proceedings | 2010