Exploiting unmeasured disturbance signals in identifiability of linear dynamic networks with partial measurement and partial excitation

Identifiability conditions for networks of transfer functions require a sucient
number of external excitation signals, which are typically measured reference signals. In this abstract, we introduce an equivalent network model structure to address the contribution of unmeasured noises to identifiability analysis in the setting with partial excitation and partial measurement. With this model structure, unmeasured disturbance signals can be exploited as excitation sources, which leads to less conservative identifiability conditions.