In dense electronic warfare environments, numerous emitters can be active simultaneously and an interleaved stream of pulses in natural time of arrival order is received by the Electronic Support Measures (ESM) receiver. It is the task of the ESM system to de-interleave this mixed pulse sequence and thus to identify the surrounding threatening emitters. In this processing, pulse repetition interval (PRI) modulation recognition has a significant role due to the fact that it can reveal the hidden patterns inside pulse repetition intervals and thus help identify the emission source and its functional purpose. In this paper, we propose new wavelet-based features for the recognition of jittered and stagger PRI modulation types. The recognition of these types are heavily based on histogram features. Experimental results show that the proposed feature set have very high recognition rates and outperform histogram based methods.