  The least squares (LS) estimator and the best linear unbiased estimator
(BLUE) are two well-studied approaches for the estimation of a deterministic
but unknown parameter vector. In many applications it is known that the
parameter vector fulfills some constraints, e.g., linear constraints. For such
situations the constrained LS estimator, which is a simple extension of the LS
estimator, can be employed. In this paper we derive the constrained version of
the BLUE. It will turn out that the incorporation of the linear constraints
into the derivation of the BLUE is not straight forward as for the constrained
LS estimator, but the final expression for the constrained BLUE is closely
related to that of the constrained LS estimator.
