Effective computation algorithms for fusion estimation

In this paper multisensory distributed fusion estimation algorithms are considered. We state new formulas which address the computation of matrix weights arising from multidimensional fusion estimation problems. This paper provides two computationally effective algorithms for computation of matrix weights. The first algorithm is based on Cholesky factorization of a cross covariance block matrix. This algorithm has low computational complexity and it is equivalent to the standard composite fusion estimation algorithm as well. The second algorithm is based on special approximation scheme for local cross-covariances. Such approximation is useful to compute matrix weights for fusion estimation in multidimensional-multisensor environment. Subsequent computational analysis of the proposed fusion algorithms is presented with a corresponding example showing the low computational complexities of the new fusion estimation algorithms.