The process of combining data and estimates is inherent in estimation problems. This paper focuses on the linear fusion under the assumption that only some elements of the cross-correlation matrix of the estimation errors are known. Configurations of the knowledge are discussed individually for up to five estimates. For an arbitrary number of estimates, a general construction of upper bounds of the joint mean square error matrix is proposed. Last, the relation with the Split Covariance Intersection fusion is discussed.