One-shot blind identification of LTI systems

In this paper we consider the blind identification problem of a single input single output (SISO) linear system. We exploit output oversampling to estimate the system parameter without statistical information on the unknown input signal. The identification problem is formulated as a suitable semi-algebraic optimization problem that can be solved through computationally efficient convex relaxation techniques. The proposed approach provides a one-shot estimation of both the system parameters and the unmeasurable input sequence. A numerical example is given to show the effectiveness of the proposed approach.