Addressing the difficulty of identifying small unmanned aerial vehicles in complex electromagnetic environments, a frequency hopping signal estimation and sorting method based on improved connected region labeling was proposed. Energy threshold statistical method, based on local windows, was adopted to denoise in time-frequency domain. Conventional connection region labeling method was improved, and a new connection region fragment association and interference suppression method was designed to solve the problem of connection area breakage and interference mixing. Reconstruction of connection areas using time-frequency amplitude differences for mixed multi FH signals. Parameter extraction and signal sorting identification based on improved connected region labeling map. Simulation was showed that in environments with noise, interference, and multi FH signals aliasing, accuracy of signal parameter estimation and probability of correct identification of the target were significantly higher than conventional connected region labeling methods.