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In this paper, low-complexity distributed fusion filtering algorithm formixed continuous-discrete multisensory dynamic systems is proposed. Toimplement the algorithm a new recursive equations for local cross-covariancesare derived. To achieve an effective fusion filtering the covarianceintersection (CI) algorithm is used. The CI algorithm is useful due to itslow-computational complexity for calculation of a big number ofcross-covariances between local estimates and matrix weights. Theoretical andnumerical examples demonstrate the effectiveness of the covariance intersectionalgorithm in distributed fusion filtering.

Low-complexity Fusion Filtering for Continuous-Discrete Systems