Abstract:The stochastic subspace method is a linear system identification method developed in recent years, which can effectively obtain modal parameters from the response of structure under ambient excitation. The data-driven and covariance-driven stochastic subspace identification methods traditionally were thought, theoretically and practically, to be consistent with each other for modal identification. However, the difference in practice between the two methods exists. Therefore, the reasons of the performance difference were analyzed and numerical study was conducted. Results demonstrate that data-driven stochastic subspace identification method outperforms the covariance driven subspace identification method not only on accuracy of identification parameter but also on capacity of identifying weaker mode.