After receiving emitted signals from various radars by electronic support measures (ESM) system, several processes are applied to signals such as: deinterleaving, recognition of pulse repetition interval (PRI) modulation, PRI estimation and etc. Indeed, recognition of PRI modulation is an essential task of ESM system. In this paper a novel and robust method for recognition of complicated PRI Modulations is presented. This method uses specifications such as distribution related to members of sequences obtained from first and second order derivation of TOAs around a constant value and continuity of these sequences to recognize the PRI modulation. Some numerical simulations are performed to illustrate the effectiveness of proposed method. Simulation results show high robustness of proposed method against noise (spurious and missing pulses) and unwanted jitter.

This letter presents a novel method based on sparsity, to solve the problem of deinterleaving pulse trains. The proposed method models the problem of deinterleaving pulse trains as an underdetermined system of linear equations. After determining the mixing matrix, we find sparsest solution of an underdetermined system of linear equations using basis pursuit denoising. This method is superior to previous ones in a number of aspects. First, spurious and missing pulses would not cause any performance reduction in the algorithm. Second, the algorithm works well despite the type of pulse repetition interval modulation that is used. Third, the proposed method is able to separate similar sources.