Aiming to the problem of difficult construction of damage index and uncertainty of damage estimation in quantitative identification of damage localization of composite materials,this paper proposed a Bayesian update algorithm of estimating damage states based on recurrence quantization feature (RQA) observation. Without referring to the baseline signal in undamaged state, the method used the RQA features of sensed Lamb wave signal to observe the internal damage from the perspective of structural nonlinear dynamics, and performed sensitive feature screening based on the correlation and monotonicity between the features and the delamination location morphology. Combining the linear or nonlinear correlation between the RQA features of each sensing path and the delamination location and shape parameters, a quadratic interaction model between the features and the parameters was established. Considering the uncertainty of damage observation by RQA features, the observation model of delamination damage was built, based on which the Bayesian update algorithm was used to estimate the delamination damage location. The simulation results showed that the proposed method could simultaneously achieve quantitative assessment and accurate localization of internal damage in composites structure without analyzing the complex interaction mechanism of structural damage and Lamb waves, and the estimated damage location size was generally consistent with the damage parameter settings of the simulation model. And the estimated damage location size is within the 75% confidence interval of the damage parameter setting value of the simulation model, and the damage estimation imaging area is consistent with the simulated damage area. The experimental results verified that the damage area and size obtained after 24 iterations of update by this method completely cover the real damage detected by X-ray scanning. The proposed method fully takes into account the uncertainties in the damage assessment of composite panels and is more suitable for the engineering practical application of damage detection and assessment of composite structures, and has good application prospects.