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

Abstract EN

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.