Invariance of subspace-based estimators

Subspace-based estimates, i.e., estimates obtained by exploiting the orthogonality between a sample subspace and a parameterdependent subspace, have proved useful in many applications, including array processing and system identification. The purpose of this contribution is to complement the already available theoretical results generally obtained in specific contexts. We discuss the generalization of the optimal weighted subspace fitting approach introduced by Viberg in the DOA estimation context, we exhibit some invariance properties of optimally weighted estimates, and we show the equivalence between subspace fitting and subspace matching.