This paper proposes a novel parametric output-only modal identification method, termed parametric complexity pursuit (PCP), for accurate identification of modal parameters in civil engineering structures. The proposed method extends the complexity pursuit (CP) algorithm through a system representation. Unlike the standard CP approach, which extracts modes individually, the PCP algorithm transforms CP into a parametric formulation that enables global identification of all modal parameters of interest. This parametric framework provides a rigorous theoretical foundation aligned with structural dynamics and explicitly accounts for mutual influences among different modes, thereby enhancing both accuracy and robustness. Numerical experiments on a simulated 3-DOF system under various damping conditions and closely spaced modes demonstrate that PCP maintains consistent identification accuracy across all damping levels, exhibiting true damping-independent performance. In contrast, conventional CP suffers from marked accuracy degradation as damping increases and fails to properly identify the closely spaced modes. Application to the HCT building further confirms the practical effectiveness of PCP, with comparative analysis demonstrating its superiority over existing output-only techniques in modal separation capability and identification accuracy. The proposed PCP method offers a robust and theoretically grounded framework for output-only modal identification, particularly advantageous in challenging scenarios involving high damping and closely spaced modes.
Li et al. (Wed,) studied this question.