Blind identification of IIR systems based on special SIMO model

Based on oversampling the system output, this paper presents a deterministic approach to blind identification of fast changing infinite-impulse-response (IIR) systems. The contributions of this paper are: 1) we prove that oversampling the output of a single-input-single-output (SISO) IIR system is equal to transforming the SISO IIR system into a single-input-multiple-output (SIMO) IIR model with all subsystems have the same autoregressive (AR) coefficients. Based on this model, a new identification algorithm is proposed, which can give the least-squares approach; 2) we show that in the SIMO model, the number of subsystems can be varied and will affect the identification performance. We also discuss how to choose a proper subsystem number to guarantee the best performance; 3) we deduce the sufficient and necessary conditions for the system to be identifiable associated with the proposed algorithm. Since the proposed approach only needs a small quantity of data samples, it can be used for fast changing IIR systems. Computer simulations give some illustrative examples.