In this paper we consider low-rank estimation of room impulse responses (RIRs). Inspired by a physics-driven room-acoustical model, propose an estimator RIRs that promotes structure for matricization, or reshaping, the estimated RIR. This prior acts as regularizer inverse problem estimating RIR from input-output observations, preventing overfitting and improving accuracy. As directly enforcing ...