Covariance intersection

Covariance Intersection (CI) is a technique used in the field of Bayesian estimation and data fusion, particularly when it comes to combining estimates and uncertainties from different sources with potentially inconsistent or non-coherent covariance matrices. The basic idea is to merge these estimates in a way that preserves the integrity of the uncertainty information. In traditional Kalman filtering, a common approach is to simply take the average of multiple estimations.