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This paper continues the research devoted to the design of numerically stablesquare-root implementations for the maximum correntropy criterion Kalmanfiltering (MCC-KF). In contrast to the previously obtained results, here wereveal the first robust (with respect to round-off errors) method within theCholesky factorization-based approach. The method is formulated in terms ofsquare-root factors of the {\it covariance} matrices, i.e. it belongs to thecovariance-type filtering methodology. Additionally, a numerically stableorthogonal transformation is utilized at each iterate of the algorithm foraccurate propagation of the Cholesky factors involved. The results of numericalexperiments illustrate a superior performance of the novel MCC-KFimplementation compared to both the conventional algorithm and its previouslypublished Cholesky-based variant.

On the stable Cholesky factorization-based method for the maximum correntropy criterion Kalman filtering