New paper: Square Root Sigma Point Information Filtering

Recently I have a paper accepted in IEEE Trans. on Automatic Control, which is a great journal. The paper is titled as "Square-Root Sigma-Point Information Filtering". The preprint version of this paper is available HERE. The abstract of this paper is following:

Abstract—The sigma-point information filters employ a number of
deterministic sigma-points to calculate the mean and covariance of a
random variable which undergoes a nonlinear transformation. These
sigma-points can be generated by the unscented transform or Stirling’s
interpolation, which corresponds to the unscented information filter (UIF)
and the central difference information filter (CDIF) respectively. In this
technical note, we develop the square-root extensions of UIF and CDIF,
which have better numerical properties than the original versions, e.g.,
improved numerical accuracy, double order precision and preservation of
symmetry. We also show that the square-root unscented information filter
(SRUIF) might lose the positive-definiteness due to the negative Cholesky
update, whereas the square-root central difference information filter
(SRCDIF) has only positive Cholesky update. Therefore, the SRCDIF
is preferable to the SRUIF concerning the numerical stability.