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Multisensor Estimation Fusion of Nonlinear Cost Functions in Mixed Continuous-Discrete Stochastic Systems

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  • Il Young Song
  • Vladimir Shin
  • Seokhyoung Lee
  • Won Choi

Abstract

We propose centralized and distributed fusion algorithms for estimation of nonlinear cost function (NCF) in multisensory mixed continuous-discrete stochastic systems. The NCF represents a nonlinear multivariate functional of state variables. For polynomial NCFs, we propose a closed-form estimation procedure based on recursive formulas for high-order moments for a multivariate normal distribution. In general case, the unscented transformation is used for calculation of nonlinear estimates of a cost functions. To fuse local state estimates, the mixed differential difference equations for error cross-covariance between local estimates are derived. The subsequent application of the proposed fusion estimators for a multisensory environment demonstrates their effectiveness.

Suggested Citation

  • Il Young Song & Vladimir Shin & Seokhyoung Lee & Won Choi, 2014. "Multisensor Estimation Fusion of Nonlinear Cost Functions in Mixed Continuous-Discrete Stochastic Systems," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-12, April.
    • Handle: RePEc:hin:jnlmpe:218381
    DOI: 10.1155/2014/218381
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