Multisensor estimation fusion of nonlinear cost functions in mixed continuous-discrete stochastic systems
type: Item
instance of: scholarly article
title: Multisensor estimation fusion of nonlinear cost functions in mixed continuous-discrete stochastic systems
zbMATH Open document ID: 1407.93393
DOI: 10.1155/2014/218381
author: Erdal Karapınar
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: 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.
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 62M20
zbMATH DE Number: 7015931
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/218381
OpenAlex ID: W2050152479
Wikidata QID: Q59063945
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description: scientific article; zbMATH DE number 7015931