A new pulse deinterleaving algorithm based on Multiple Hypothesis Tracking

The main function of ESM is to receive, measure, deinterleave pulses and then identify alternative threaten emitters, among which pulse deinterleaving process is significantly difficult and important. Dense electromagnetic environments cause an ESM to receive a seemingly total random pulse stream with large noise. The traditional algorithms have behaved weak and unstable under the rather severe situation, so we propose a new pulse deinterleaving approach based on Multiple Hypothesis Tracking method in target tracking system. Simulation results have shown that the algorithm can perform PRI estimation and pulse recognition with high precision. Moreover, the algorithm is proved to be considerably robust and reliable even with large observation noise and PRI jitter at a missing rate up to 25%.