On linear estimates, minimum variance, and least-squares weighting matrices

Some well-known results on unbiased linear estimates for linear observation models and a priori mean and covariance information, with minimum variance and least-squares criteria, are compactly rederived. The procedure involves the use of a gradient matrix formulation for a parameter optimization on the gain matrix of the estimator.