Almost all military systems use electronic guidance equipments. So, electronic warfare against the electronic equipments of the enemy hinders or weakens their proper operation. But, most important and most basic step in electronic warfare depends on sufficient knowledge about their radiations and activities in the electromagnetic spectrum. On the other hand, enemy tries to destroy our electronic systems through intercepting and aggregating information about these systems. To detect enemy’s measures and maintain our electronic equipments efficiency, complete awareness of the environmental radiations is required. To do this, it is necessary to intercept all electromagnetic radiations from all present emitters in environment via Electronic Support Measures (ESM) systems. But, using a single channel by numerous electromagnetic emitters leads to a random interleaved pulse train at the ESM input. Therefore, it is necessary to de-interleave the pulse train at the ESM receiver. After that, the analysis of de-interleaved pulse trains for identifying the emitters in the environment may be started. Any errors in de-interleaving step, lead to errors and efficiency degradation in the analysis step. A de-interleaving algorithm must determine which source produces each intercepted pulse. The optimum de-interleaving algorithm examines all possible active source sequences. But, high computational complexity of this algorithm makes its implementation practically impossible. In this thesis, in addition to describing electronic warfare systems, especially ESM systems, different methods of pulse train de-interleaving are examined. Also, a new algorithm is proposed that in addition to high efficiency, has less complexity than exhaustive search. Also, it may be improved to withstand to the problems like missing or spurious pulses, new emitters activation, present emitters dormancy, and time axis segmentation.
