Automatic Detection of Multiple Morse Signals Based on Broadband Time-Frequency Diagram

Current algorithms don't cover the multiple Morse signals detection in broadband environment. To solve this problem, an algorithm based on broadband time-frequency diagram and ensemble learning classifier was proposed. Firstly, a fast narrow band signal filtering method based on broadband time-frequency diagram was proposed to realize the fast filtering of narrowband time-frequency signals of various types of signals in the noise background. Then, in order to identify the Morse signals, a new feature vector was proposed which was combined with three new features and local binary pattern (LBP). Finally the ensemble learning algorithm was used to design the classifier to realize the automatic detection of Morse signals. The experimental results show that the correctness of the algorithm is above 95% and the error rate is below 10%, which has good robustness and application value.