To address the challenges in the quantitative damage evaluation and the uncertainty in damage evolution of composite laminate structures, a fatigue damage evolution tracking method for composite laminates based on multi-feature interactive fusion is proposed. This paper proposes a method for tracking the damage state of composite plates by constructing a damage index observation equation based on the interactive fusion of multi-domain features, combined with a strain energy release model and a particle filter algorithm. By extracting multi-domain features of Lamb wave signals, such as time-frequency domain features, dynamic time warping features, and transfer entropy features, the fatigue damage state of composite plates is comprehensively characterized. These features are used as observations of the damage state, and a damage state space model for the composite plate is established. To better capture the linear correlation between multi-domain features and the degree of damage in the composite plate, a multivariate interactive prediction model is innovatively introduced to fuse the multi-domain damage features interactively. This establishes a mapping relationship between Lamb wave signal features and the damage evaluation index of the composite plate, forming the damage index observation equation. Building on the strain energy release rate model of the composite plate and considering the uncertainty factors in damage evolution, the particle filter algorithm is employed to track the damage state, such as crack density and delamination size. The effectiveness and accuracy of the proposed method in tracking and predicting the damage state of composite plates are validated through finite element simulations and fatigue test data analysis of composite plates made from T700G unidirectional carbon fiber prepreg. This research not only reveals the evolutionary of the damage index but also provides a new technical approach for real-time monitoring and evolution prediction of damage in composite plates.