Abstract: Stochastic subspace identification （SSI） generates spurious modes in the process of identifying the dynamic characteris? tics of high?rise structures， which interferes with the automatic tracking of dynamic characteristics. This article has proved that the non?white noise excitation is one of the causes of spurious modes， and further proposed a signal reconstruction method based on multivariate variational mode decomposition （MVMD） for non?white noise excitation， which removes the influence of non?white noise excitation in signals and eliminates spurious modes. A Single?Pass clustering algorithm is proposed to eliminate discrete spuri? ous poles. The above algorithm has been applied to on?site monitoring data of super high?rise structures， achieving long?term auto? matic identification and tracking of dynamic characteristics.