To address the issue of data loss commonly faced by tip timing systems in practical applications, a method for identifying missing tip timing data based on Correntropy Matching Pursuit is proposed. This method uses Correntropy Induced Metric based on Gaussian kernel functions to measure sample weights. Unlike orthogonal matching pursuit, which assigns the same weight to all observed data, Correntropy Matching Pursuit assigns weights of different norm types to the observed data based on changes in correlated Correntropy Induced Metric, making it more robust to outliers. The performance of this method was verified through simulations and experiments. The results showed that the correntropy weight factor assigned nearly zero weights to the missing data locations, effectively reducing the impact of data loss on fea? ture extraction results, thus demonstrating the robustness of the method. The tip timing data loss identification method based on Correntropy Matching Pursuit provides a theoretical basis for the implementation of tip timing systems in practi? cal applications.