Asymptotic variance of a certain closed-loop subspace identification method

In this paper we study the asymptotic properties of the "innovation estimation" algorithm by Qin and Ljung. We derive expressions for the asymptotic error and decompose it in a "bias" term plus a "variance" term. The asymptotic variance formulas are rather complicated in the general case. We report expression under a simplifying assumption.